{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy, scipy, matplotlib.pyplot as plt, sklearn, urllib, IPython.display, stanford_mir\n",
    "plt.rcParams['figure.figsize'] = (14,5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[&larr; Back to Index](index.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic Feature Extraction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Somehow, we must extract the characteristics of our audio signal that are most relevant to the problem we are trying to solve. For example, if we want to classify instruments by timbre, we will want features that distinguish sounds by their timbre and not their pitch. If we want to perform pitch detection, we want features that distinguish pitch and not timbre.\n",
    "\n",
    "This process is known as feature extraction."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's begin with twenty audio files: ten kick drum samples, and ten snare drum samples. Each audio file contains one drum hit.\n",
    "\n",
    "For convenience, we will use `stanford_mir.download_drum_samples` to download this data set at once."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "kick_filepaths, snare_filepaths = stanford_mir.download_drum_samples()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read and store each signal:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "kick_signals = [\n",
    "    librosa.load(p)[0] for p in kick_filepaths\n",
    "]\n",
    "snare_signals = [\n",
    "    librosa.load(p)[0] for p in snare_filepaths\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Display the kick drum signals:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0QAAAE5CAYAAACwOuAYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsvXmUXNd93/l5a+29orFvBAEChCjuWkyLFEVLMmUtXkLL\nlBPJyWHGWU6SccaeROdkxsfWTEaKE59JzjgaO44d23FsOrKiOTQtWRLFRRQpiAAJggRA7EBj6b27\n9uVt980f971X1VgIsIHqKqLv5xwS3VXdhduFX997f9v3p4VhGKJQKBQKhUKhUCgUKxC91wtQKBQK\nhUKhUCgUil6hHCKFQqFQKBQKhUKxYlEOkUKhUCgUCoVCoVixKIdIoVAoFAqFQqFQrFiUQ6RQKBQK\nhUKhUChWLMohUigUCoVCoVAoFCuW63KIDhw4wOc///lLHn/22Wd57LHHePzxx/na1752PX+FQvG2\nKBtU9APKDhX9gLJDRa9RNqh4t2Iu9Rt///d/n6eeeopcLrfocc/z+MpXvsLXv/510uk0n/vc53jk\nkUcYHR297sUqFJ0oG1T0A8oOFf2AskNFr1E2qHg3s+QM0ZYtW/id3/kdLp7revLkSTZv3kyhUMCy\nLO677z727t173QtVKC5G2aCiH1B2qOgHlB0qeo2yQcW7mSU7RB//+McxDOOSx2u1GoVCIfk8l8tR\nrVaX+tcoFFdE2aCiH1B2qOgHlB0qeo2yQcW7mRsuqlAoFKjX68nn9XqdwcHBt/2ei6MJCsX1sBQb\nBGWHihuL2gsV/YCyQ0WvUWey4t3AknuIrsS2bdsYHx+nXC6TyWTYu3cvTzzxxNt+j6ZpzM72Plow\nNlbo+Tr6YQ39to53ylJsEPrDDvvpfVfraK9hKSx1L5yeruAHAk0Dy7w02roc9MP73i/r6Ic1xOtY\nCtd7JjtugAhDMqkbfl24Kv3w3vfDGvptHe+U6z2T/UAAYBrLL4zcT++7Wkd7Dd3gunc4TdMAePrp\np2k0Gnz2s5/li1/8Ik888QRCCB577DFWr159za/3/714ip95cNv1LkuxgrjRNgjwX799lM//5M5u\nLFdxk3Kj7HCm1OSVw9PMV1r8vZ+6vdvLVtxk3Mj98PsHJijXXcaG0nxw99puLltxE3Gjz+TDZ4q0\nXJ/3376mW0tWKNDCPslJfuelU9iWwW//xev84Rcf6cka+sXz7fUa+m0dy8nsbBXHC/hHv/1CT+yw\nn953tY72GpaTl/efY/+xOf7mlbMrei/sl3X0wxridSwns7NV/uhbb3H4TJGP3r+Rj79v87L+/dAf\n730/rKHf1rGczM5W+ef/zw/4xAc28/H3r0wbVOu4dA3doG8Gs/7gzUneGl/o9TIUCoIoPa9Q9IL/\n+I2DLFRbvV6GQoEQIXPlFk9+70Svl6JYwfzEfRsZGUj1ehmKm5y+cYi8QHByotLrZSgUzJVb3LJu\neaNgCkVMpe6iRyUnfZLAV6xQfvDmFAB33qrmxSh6R8rSmVpo9noZipuc5e+SvAKzxSbTRWXwit5j\nWwaFjN3rZShWKHdtH8UyZazK9QQpuzfCCgoFSGdo95bhXi9DsYLxRUjKUvugorv0TYbI8YJeL0Gh\nAEAIAVqvV6FYqezaPMyqoTQgM+cKRS/ZuWmI51+f6PUyFCuYIAgRqGy5orv0jUO0Zjjb6yUoFAC4\nvlD+kKKnCCEPf1cFihQ9xvECak2v18tQrGCCMCRUsSFFl+kbh+j+Xe9MFlmh6BZzpRYLVafXy1Cs\nUMIQ/EA6REL1ECl6zOR8g4bj93oZihXKW2cWECJU/ZSKrtM3DtHYUAZNheUVfcALr0/g+SocpegR\nWogfCCxTQ6g7gKLHHDq9wKM9kDtWKAD2HJ4mDEMCtRkqukzfOEQQ8n6VJVL0AZapU8havV6GYoUS\nClkyJwSE6hKg6AN0FaxU9IgwBEIIhApSKrpL3zhEL7w+gWHI5ajUqKKX3LdzjGxaCjD+6XeO9ng1\nipVIIELpFKm9UNFjQkKUGSp6xY8OT1Opuyh/SNFt+sYh2n98DkPXyKRMpTin6ClhKC8Ani949rUL\nvV6OYoURhiF+EBIi1ZUUil6ybf2gClIqeoYXCDJpU5XMKbpO3zhEI4UUZ6drNB2fRks1cCp6x94j\nM/iBYGqh0eulKFYgYQhBJLf9xsm5Hq9GsVJpufIcnlloMK9EZhQ94v5dYypbrlgW+sYhAvB8mRky\nVMGyooe8d9soLTfADwTbNwz2ejmKFYYfiCQaumoo0+PVKFYi41MVmo48j0cG0ypDpOgZ+47MIsJQ\n9VMquk7fOEQhMJRPoesaunKIFD0kDME0NMo1V82BUSw7Ie0GYlUyp+gFe6O+DYDBrE02rURmFL1D\nhHIWkULRTfrGIQLQdA0N1DxiRc8JQxgu2OSV2pximREdc4iUspKiF3RmhKaKDZUhUvSUMGwPq1Yo\nukXfOETFqsNCpQWoqKiit4hIVemVt2aYL7d6vRzFSiNsDyFUlwBFrzk7XVMOkaKnhGGo9kJF1+kb\nhwjkRGwRhklDsULRC0QgBx9sWzfAyGC618tRrDDCEOIt0FeXAEWPSVm6kt1W9JQwVKIKiu7TVw4R\nACHK8BU9RYRS8nhyoYHqZlMsO1q7ZMn3VXBI0Rtars/akSyrhjKqjF3RM3ZsHGS21FJOuaLr9J1D\npGZvKHpOCKEI5XBWZYqKHhAHhVQjsaJXfP2FU0wtNJgtNvFV1YaiR4ShHMuitkJFt+kbh8g0NFZH\nErOOr5S9FL0jRDa2l6qOKllSLDudDcSqd0PRK05cKAPRfqiClIoeUWt6CFUyp1gG+sYhsi2DXMYE\n4NUjsz1ejWIlE2++uYyFUCpfimUnJDa7UJmfosesHckiVKpc0SOyaZOwQ2hGoegWZq8XEGMZejJ/\nSEkdK3rJ2elq0sSp9mDFstPRR6nMT9FrsilT7YOKniJC0NRuqOgyfZMh+vH3rks23VVK2UvRQ9aP\n5qg3fdlLpG4Cih6QOETK/hQ9JkTZoaJ3tFwfzxcqW67oOn3jEAGJQ+SremVFDxEh2JaO5wtUL7Gi\nF8Q9RKpuXtFrWq6vMkSKnlGuubh+oPJDiq7TRw5RSNPxAXBcv8drUaxsQkQIvhAIFZZSLDOdEXnV\nwqboNRNz9eRjlSlSLDe2ZWDouhrMqug6S+ohEkLwG7/xGxw7dgzLsvjX//pfs3nz5uT5P/qjP+Iv\n//IvGR4eBuBLX/oSt9xyy1Vfd2qhAahhhIproxt2OFNsyGhoCJqmLqSKt6cre6Ems5QAgTJAxTXQ\nrTPZNNqT2GpNj3/2H17kD7/4yI3/ARTverplg8Wqw8axHIG6Fyq6zJIcomeeeQbP83jyySc5cOAA\nX/nKV/jqV7+aPH/o0CF+67d+i927dy9pUSoIpbgWumGHX/y9PTz6/s0ySi9UU7vi7enKXhi27c5T\ng1kV10A3z+TBnI0IQ/7tn++/kUtW3GR00wbDUJUPK7rPkhyi1157jQcffBCAu+66i4MHDy56/tCh\nQ/zu7/4uc3NzPPzww/zyL//yVV9zX4fUtkrLK66FbtghQIiU+AxEqGS3FW9LN2yws2SuWHNu+JoV\nNx/d2gsBchmLWsPj9i3DlOvuDV234uahmzYowlBFJxVdZ0k9RLVajXw+n3xuGMaii+MnP/lJvvSl\nL/HHf/zHvPrqqzz//PNXf82ml3ys/CHFtdANOwRpf/HcA2WLirejGzYoZd/lx/m0GkGguDrd2gtj\nAhFy/HyJkULqkueOnS8ued2Km4du2qAQIaEI+daecYpVFSRSdIclZYjy+Tz1ervRUgiBrrd9q1/6\npV9KfjE+/OEPc/jwYR5++OG3fc2feP8m/urF0wDkcjZjY4WlLO266dXf229rgP5Zx5Xohh3eumGQ\nVNpC0/XoT23Z34d+ed/VOq5ON2zwzFSV0Wj0gJ2yVvReCP2xjn5Yw9vRDTsEMAwd09AZyKcoVR28\nILjkvfi3T77Ob/3TzVd4heunH977flgD9M86Lke3bBDAtAx0XePgmSIP3bdJnck9pl/WcaNZkkN0\n77338txzz/GJT3yC119/nZ07dybPVatVPvOZz/DXf/3XZDIZ9uzZw2OPPXbV1zxwbJaRgRQLFYdq\n3WF2trqUpV0XY2OFnvy9/baGflvHleiGHZ68UGbrmjxBENBouPi+WNb3oZ/ed7WO9hquRDdscMeG\nQWZKTQCaTXfF7oX9so5+WEO8jivRDTsEcL0AzwtwHJ960yMMw0veC88Luvb+9MN73w9r6Ld1XI5u\n2SCA6/hoGgzkUpybKJOzlk8guZ/ed7WO9hq6wZIcoo997GO89NJLPP744wB8+ctf5umnn6bRaPDZ\nz36WX/3VX+ULX/gCtm3zwAMP8NBDD131NWdLTfIZG4AgCDk9WWF0MM1A1l7KEhUrgG7YIUC9Jedu\nnJ6sqkZOxdvSDRscKqSYKja6vXTFTUS39kKAct0ln7G4fcswB0/NX/K8GpOhgO7aoOyrhKF8ipLq\nq1R0iSU5RJqm8Zu/+ZuLHuuUT/zUpz7Fpz71qSW8srx8Ti80+MvnTwIoiU/FFemWHbbcABGGDBds\n5spNwjBE07Srf6NixdG1vTBc9IdC8bZ0yw7DEDJpExHCmyfnEYQIEaLrcj8UIsRVSogKunkv7BTa\nCpPxLArFjaaPBrO2D/9GS0WcFL1B06DScBECLMNAiFDNP1AsK2EYJnuhSlAqeknGNiCUWaLtGwfw\nfUHLDZLnXT/AV0qcii5SyFiR7LYU97Ato9dLUtyk9JVDFN8CxqdlfWI2vaQElkKxZMIQsimTMAwR\n0cX05IUyz+w71+ulKVYS4SUfKBTLjmnq1FoeEBIEIV4Q4vpth8jxBEEgs0adNB0V1FTcGDRdk2dx\nGFKquQSB2hMV3aEvHKKJuRpNp73JbliVA+Du7auSx7yOTVih6CbTRdnQHggpu/36iTm+uWe8x6tS\nrBhCOQsLpIM+FwksKBTLhRNngUJotnwyKQs/CPH9YFEFh+cHeL5Y5CQB/N5Th1T/peK6abQ8KnUX\nIUKEANvUCVRGUtEl+sIhmp6XNaH1aKM9eHoBgJMTZUBGm/7Bv3uB4+dLzJXV5UDRXVquHw1mFQSB\n4PDpBVYNZnq9LMUKofMaWam7fP2FU4uePz1ZXt4FKVYcf/HMMSAaUg0QhrJ/KFwsouAHIZ4v2g5U\nRNPxqaohrorrJC5XF0JaohcIfJUhUnSJvnCI4n71OM1eyMphhLHCXKPlc/f2VTz10hlePTrbkzUq\nVg4jA2kCIdUORQh3bBtly5r81b9RobhBxMF1y9RpdVxAAyH49iuqfFOxPIQdf3qReILjtSP0juvj\nC4HrC/7TU4eSxz1fsKAGaCquE0PXyKQMgmhYuizPVBkiRXfoD4cI6RHFPUOlmowszVdaAFSbLqah\nsX3jIErrS9FNMh39Q/F/fiCoNT0ADkfZS4WiW4QszhKdmqwkKkstN7ikX0Oh6Bad560fxA5ROxsk\n7VE+duJCOdknwxBmig1qTZd6U2WKFNeHEEIKK4gwmdGmUNxo+sIhmpyX041tUy4njsaPRdPaqw0P\nNA3PDZINV6HoBq4X4HqCkLa6nB+EOFF09Lf/++vqQqroLvHQjejDasNjMiordtxAqR4qlg0RQj5j\ny8CQ33bKY5pR9rLR8ilkLQ6fkQEjLxBUGx6vvDXDq8fmln/hipsCuQ1qCEGkNBeSuozK3B/+9VvL\nvjbFzUdfOERvRZtoXCYSn/fxwV+puxDK+lF1GVB0k0BEcw6izTcMQzw/wDJkrHTnpqFFFwKFohvE\ne2EoQtaOZJmKHKKG4yuHXLF8hKAR4npB0szeKaDQisSQ6lGg8uCpyCHyBY4X0HR8FcRULJmkf00I\nRBgShCFOh/19a884jhdwfrbWszUqbh76Qtf62Nnios/jAz92fpxoUKbrC3x1GVB0mbGhDAuVpnSK\nRIgfhJRr8lB3PUGj5SlJeEXXSBrZkU55NmXw6rFZ7t05RqXudjyrUCwPhq4ngUqvYxCrF5XRNV0f\n1xOU6w5hGOIHgSytC2k3CSsUS0REPURChFyYrSeP//DQVPRcDxenuGnoiwzRxRHP+LPEIfKktGcQ\nhHieaqhTdI91o1k0jaReWYTgC4FtyV8VEYa0vICjFznxCsWNIhRh0jMURsMIN4zJUQRNN0hKlxSK\n7tO2tSByfjpVvmLnqOUG+IFgoeLgR0pgnifFFlzv8hn14+dLnJ6odHHtinc9YQiatMIgiO6KHdvf\n3TtWMb1Qx/GCZM9UKJZKXzhEFxMbdmemKAhk2v7ieQcKxY1krtRKpmKHHRHRuKEYZL38v/mz/T1a\noeJm50dvzSQfh2Eo+4Yi+3PdAF+pLCmWmZB2gNLzA944Mcd39p5Nzmg/kLOImq6P4wl8P3KG3sYh\nOjxeTEZsKBSXI1E5jAelX+T0BEHIutEcXiBUKbviuukPhyjKqJejuQVx1CmIIqV+1Dvkh2KR5KdC\ncSNpOT5eIJJNN4iVvZyAZrTZen5AqeYylE8t+t79x2dVhEpxQzANPXHGgzBE0zQa0UgC15eqXgrF\ncpDsaNGFFOS5/AfffIv9x+eSM9v1ZFao2fIpVh18IecTxYNbL0e94VFTCnSKqxBGwckwmoNVqrmJ\nEFel4eL4Ab6vHCLF9dMfDtFFxFmgIAj5i2dP4AdyYxUBuB0zORSKG0nc/Bsf8nH0s+UGhCJ20qFY\naWGa0oufiyRA//yZ48lgYYXi+rioZC4M8aNLpReIpG9Doeg2YdiWgY9t0g8EQ/kUubRJORqR0YrU\nD5tuwHylFWWIpDPk+oJj50rMFBuLXrvpBjQddYlVXBk/ClCKyBADES6SfSeUPeZ+IBY/rlAsgb5w\niC4OrFuGXJYfCF49OoPjCQIhezkuvnSW1TRsxQ2mkJGDgYOoVl7XNepRhN7zBeWGS6Pl4weCf/G7\nPwQgl7Yo19QgQsX10zmHSIp6tJ0g3w+TEqT5cvOK0XeF4oYQl693HNL1lo9t6gQiTIYGu36Q7Jez\nxQYhcdZI2u6Rs0XeGi8SCMF3XjkLyKGu8fe/eGBiGX8oxbuFuI83ltyOh7K+cUJKuXuBiByikGqj\nfRf0A8Fv/JdXerJmxbuXvnCIJufqiz6P915fCOYrDp4vJT+DIKTa8BZdAv63398DwBsn51T6XXFd\npGwDjQ5Rj6RERBAKkkxlo+kTBIJSzWFsKJ18zVy5xa//wY8WbcwKxTumo38tEO2SYZAlm25UNvyd\nfec5N1Pt1SoVKwABEMpzN4yOXdcLQJOX1TjDI0UV5McLVRkY8gPZS+R5AtcNqNRdzs/Uee71C4AU\nS2p5UkH2u/vOLfePpngX4AdSWS6MMkRxufBcRdqY4wW4vpwbOFdqJd9XbXiMFFKXe0mF4or0hUMU\n06nkBdL4d2wcxPWkMySEjM7/+68dYHy6StPxGR2QF9IfHprihf0qyqS4PnRdk3OvaKsqBYGcgVVv\n+fgipFR38HypqOT5AhGl8RcqLfIZi/3H1SBCxY1BXgakY/T8/gvRBSCQl9IwZKGispKK7hGXzKVt\nIzmXHTdIyonjwaxyTpH8nriMzg8EngjxIgnuRsvn7EyVYtVhodKKBBcE5ZpLteEtEq5RKAD+4KmD\nidx2Z9nmyIB0dvwgTM7g+Yp0iObKTRYqLVVarHjH9JVDpEfzCtrqXgGVhkul4cpJ2VG0IJsyeeH1\nCzz72nkZZXJ95sqt5BcCpFPlqCY7xTvg7FQV09CTaHziEAnZw1FvegSBLBMRIUzM1XHcgHLdpenI\nSJXo6PdQKJZKZ79GGIIIQv70u8eSC4DjyZ4NlY1UdJOkl00sHoMBJKMwgEVKcs24vDgQBIHA8wWt\nyCGq1j1cT3D0bAnXk47S5FydetOjXHNptDxOKSluRcRrR2YSp1yEYcfZHPJnzxxLbMgP2s/9+6+9\nwUK1BaFG0/H5d08qRVjFtdFXDlEynT36U4QwlEtJ2VkRdpSNCDSkA+V4glq0mVY6LgcHjs/xP75/\ncpl/AsW7mf/jD3+E4wWkbQMgGQLsB3IgcLXh4npt1aRzMzVcXzBfbuF6QeQ0teviFYql0qnoFTcV\njw2mkwum4wU0HP+yykqVhqvmuyhuCEKEuJ6I+jekTdZbfjSKIEwk4Dsb2tuKnNHXRDbbcP0kozRX\nbuF6UpJ7ptzEFyFz5SY/PDTN9149v8w/paJfcbwgyQzFmXKQ7RTHzpYIOuS2W5EjbkRVHiIM2Xdk\nRvWZK66ZvnKI4u6NzujofKUVRQDadfTxVOx6y8cPAqYXGjQdn2aH4MLEfJ1qpBqmUFwLG1fn0TRZ\nNgeLL6W+L20xpD2YsFx3CETI+HQV1xc4fkDT8ROJZIViKcgLQPRxHB0V0ikKoihpqerQdHxcT9rc\nxFwt+f5Xj8yw7+jMZV9boXgniFBmekQYJgEiEQUn475eYJFanBepxPpRBkkKgYjEXgEajtd2lKJz\nerbUZL7cZK4slTv/w9cOLNvPqehvwlBWbMRO+YHjc2iaRiDa9vbGqXk5ON0NcFyR3B/VNAzFtdJn\nDpEkvoiGoewr8qJSpLiEyfHkALha0yUQIedn6zRaPo2OaGmcNVIorpV4CrZIDv724yHww0PTQLuU\nrt6Ujs9EJApSa3g0HF/Jfyqum3aWPCQUIW50uYwFFebKLVqObErfc2iKlw9O8+xr52k6PpW6S62h\ngkGKG0TYdsiBpDTY8wXBZTJEccAoyQ7FZXMde2PT8WUvnB8kCp61pk+57lKuu3h+wLnZGo4XJKp0\nIgyTcjzFykKWzLX3xWzaQtOiPrVoT6zUXUpVB9cLEoe7WHMo15xFdvOPfvsFGmpEhuIy9JVDFDvy\nnc2VGlpUNtIuYXKisqV6y8f3Qybm64TITbbp+Pz5M8dotPykOV6huBaajr+ocTOeSxRfBLIpWUqX\n1NJHkanZaBZRo+XjuFceRKhQXI042hl2ZMvbl8+25HalIS+NjieYXGhQqjkcGS/yw0NTNN2Aeuvy\nDtHpiYqSh1e8I0wzuibElRu+SBrZg8T5ae958cd+FNH3g1hYQST222z5ST9c7Ly3PJ9a06Pe9Dg3\nW6dcc5ldaPDCgQkqDZdnXz3P7z99GID/+u2jap9dQcT7YCLs4QXomlR3deMAZctn35EZmo6flHXW\nmx6Nlk+x5vDiGxNUGy5p2+DNU0r4SHEpfeUQxdFPLRJXgGi+gZDZoTgy73ly2FvL8fECQbFDgnHf\nkRmmF5rRL4WMEuw9MpOk4RWKK3F+RpYdxVEoy1ysejg+LZ9PDnx/cXS02vQIkbXz/+ef7FuuZStu\nIn7uXz6N54tFstueL/CFvITGkU7HlSIejutTqjrUGh61lsfRsyUcL7jikODvvzHBnsPTlzxebbic\nmVJ9R4rLE3ZIHsfOuddRxh5n1aEjQyREVOou1eQcry0Z33TlhdXzRRKtbzlBcoE9Ml4kECGnJsrU\nmh7HzpYYn64xMVfHDwT7j8/y2rHZZXwHFL1E2p9Y5BCV6q6cT9nhjB87V8KNHCHXFzRbMsh5brrK\ny29O8cy+c9RbHlMLTWpNl+f3X+jRT6ToR/rKIYoJO4o+XU/OMgg6VG78QDpDcao9PvwdN+D8bI1K\nw6XpBtRaHpW6y7dfOcv3Owa/db7+d/edQ4iQYlVFTRWS2Dpiv1xEB3zKisQWos9jWU/Xb5eBADie\nrF1uXCFKr0rqFFclHj0QyMGEflSe1Ih6Nc7NSkGPphNQjUo1G02fc9NVHFf2FZVqDl9/oS0s43gB\nJy+Uk4xmJ3/zo7P86XeOLdobFQqIGtqTnKV0dOLMj0jO5E6HqD2uwI/6L2M1sFZSMhckogtxNjPu\nvwwhcc5PnC9Rb3pMLTQoVlosVFscPrNApe5ydrrK5Fyd//iNN/EDwbf2jC/PG6LoCYFoByddT6Ch\nSTvsyBTORHtbrenhR+qGIEuM6y2PibkGfhBSqbs8+9oF9h2dQYiQb+0Zp9HyVUnmCqevHKI4L9S5\nucZSi37QbuD0AhlxikUU4gtmyw2YK7eS0iXfDzlwYo5zMzXmyi2++cMzzJWb/O9/8AqlyAF6+eAk\npybK/Js/e039MiiADqnZjig9tMuZ4s/jaGeschOX2NWaHs2Wz4tvTF7y2i8fnOLLf/pq9xavuCmI\nd8D4QPd8WZ4U22Cx6sqou+tTrju4nrxMFmsO1aZH0wnYf2yWM1NycOtfvXSarz13gvOzdUq19uDM\nmIm5BuNTVcan24Ner+TQK1YWISRnL9HHSdVGh+pXTOIQRee2J0RyZifZoEg5Ftr7ZsPxE3GGuOrj\n/HQNEUK55lCuu/h+yCtvzSBCmC+3ePXYDBdmaxw8Pc+zr11AiFDZ7U1I0lPZcRY3XX9RlhLao1tq\nTQ+vQ4Gu1lE6B1IQaaHSYqHqcOj0PHuPTPPk947x588cB2S1yJPfO86piTI/fPPSc1xxc7Ikh0gI\nwa//+q/z+OOP8/nPf56zZ88uev7ZZ5/lscce4/HHH+drX/vaO379zhil64lEcjsI27Lbcv6QNHan\nQ+a4WHVodsh77js6i+cLqnWPFw5M8o3vn2Jirs5fPHcCPxBU6h4/eHOS2WKTPQcnmS01+cb3TzE5\nX+c/P32Y14/P8uKBCaYX6iqy32d0yw7jDTZ2jOKoVCwnG1xUMteKDvG4Pr5ad3F9wULHXKznXjvP\nmckKb5yYwzYN/uDpw/zootKlUs3he6/IKOdb4wuLylAU/Um3bDC+AMTBoZYnhwLHe5AsCZHS29WG\nR9OV5XSOJ6jUXZquz/h0NVGje/nQFJPzDUA2Hx85W+SPvnUk+fvmyk0CEfLGCVlbf+pCif/jj/ep\nPo13Cd08k2WWssMhipwhL2iLKlzsMAGJMqzvh5ec2Z3Bx9hJqjbcZGRBrNQZZzNLNZdaU/YEx3Y8\nX20xtdCkWHU5fKZIsdri1WOz/MZ/2Uu57vDC/guUau09WL5P4aIeOs8XvB7ZfE2p0l43XdsPaSu+\nQpR99AUiEIsC6LHdNFo+fmRzIIWPqlF/Gsh/64n5BjMLDV49Niez7C2fo+eKNB2fvUdnOH6+xMsH\np3jxdSmDxhrDAAAgAElEQVQDL6W/QybmaskwdsXNhbmUb3rmmWfwPI8nn3ySAwcO8JWvfIWvfvWr\nAHiex1e+8hW+/vWvk06n+dznPscjjzzC6OjoVV83NutQdG6+l2vWDHH9IPlFcLz215RqLk3HxzKk\nr1esyg2xXHeoNtykD+TE+TJnp6uUaw6nJiuEwIlzJZ6bqvDGyTmmiw2OnysDUiL05YNTpG2Df/bY\nnRw4OYep69yx7dKfaXJeKo6tG83J98MXfHffWW7bNMzhMwt85sdvuer7cC3IMoZ2RGQl0i07jA1R\nJFEp+WfsAMV2mJTMdQwqBKhFEcpizeGvXjrDp398K68em+XUZIWTE+VILlRwcqLC+3atptby2Hdk\nhlMTFfYdneXTD2xh71szPHjXOn7ivk0AvPTmJM++ep5/8NPvYbiQ5uWDU7z/9tVkUvJXuN7yyKbM\nRf13IJ2sXNpK+qEUN5au7YUdKnPQzkJ2XihdX5YFNx0fw9CS5yp1OeBycr5BsdriwIk5ag0PI7KN\nUs3l9eNzzJWbvHZ0hl1bhpPIabw/PvX9U0wXmxw4Mcf9u1YDMFNsMF1s8t7L7HuK3tK1vZC27HtM\nIAQiBIuOC2pnD5Fon9OmsfiMjrM3nbPaYrst192Or4uV5+TXz1daycfxMOJS1cHQNRwv4NSFCiKE\n7+49x1y5xTP7zvPym1NcmK8zmLM5eHqBX/n5u/jWnnH2Hpnh73z8NvYcmmbNSIbn90+QsQ1+76nD\n/MrP38meQ9P89IduISQkbS/pirRi6fqZHFdn+LI/Tdc1RMcdMXZSHE/2WOpuu2Suswez0ZIz3EQI\npyYqVBoec+UWs6UWv/fUITK2wVy5Rdo2pXKsG/DvntzPbZuHOHymyIfvXs/39p3n735iF9/Ze44v\n/ORt5DL22/4Ib5yc585b2z9rpe6QTVscPlPk9i1DaJqGaegIESajPxTLy5J+21977TUefPBBAO66\n6y4OHjyYPHfy5Ek2b95MoVAA4L777mPv3r08+uij1/z6nXFxKbXYjgrEtNwguTR0Zoik3GKY9BXF\nQ7mKVYeWGyTRoflKiz//3nFE2E7PHz69wPmZKoGQzXmlmsvRcyV0LSqDcgL+8vmTnJmqoKGRsg0O\njxdJWwaVuvzajG2CBoWMxda1Bc7O1PjR4Sm2rB1grtTk/Gyd4XyKkxfK7NoyTBBp5W/fOIRt6pyc\nqnL3rSOsGkhzZLzE2lVZDp8usnvrMPOVFoO5FAdOzKHrMlJ2/67VrBpIMznfwLZ0Gi2fXMZE1zRG\nBtK8cWqeO7eNUnd87rhlBN+XIhOjg2lmik12bhpifLrKYM7mwmydu7aPUq67rKk4lMsNTl6osHYk\ni2ForBvNcXqywsaxHGcmq9xx6yi+L5grt8hnTGZKTbasHcDzBaauMb3QZMNYlmLVYXQwA8DpyQob\nVuVoeQGjA+lILUZjZqHBhrE8vpAN5ZapU6o5jI0Vlt0OYysTF2WK4s22c0AwgOPHvURRw3C06R4Z\nL3F2qsbeI9NowNRCg4WKg2XqOG5AtenxP75/iudfv0AYwlDexvUC9hyeZrbY5Huvnue2TUM8v3+C\nUxNlxqdr/LfvHqNS9xifrvLC6xd44lO388y+87x+Yo51I1k2rMoxudCg6QR8cPcavvfaeVYPZfif\nPr2bfMbi6NkSZ6YqjE/XuGfHKl58Y5JsyuAzP34LP3hzkkbL54E71rL/1DylUpMtawuMDmaoN11e\nPzHPzk1DDBdSzJdbbF03gGlohEC55hIEAsPUOTVR4fbNQ4Qgfx+i9840NCzTeNv3Ppb3NY3FDpwf\nyAMwZRl4vsC2DEQYXjUgEEYKbaahJz1hFzuN8esDl/y9V6NrNhhnJ5PyzMWR9VZUElyte4hQZilj\nu2w4PiKU9tZwAr79ytlFMrPFaosj40WqTY8/+c4xBnN28vyxcyX+5G+OJNnLw2cWGCmkGJ+p8s0f\nnsU0NL74d+5D0+A/PXWIkYE0jZZPteGyaXWez35kO3/9w3FOXCjz4bvX86PD03z8fZs4PF5k27oB\n/ECweW2ew6eL7Ng4yNrRXLSvh4DG9w9MsFBp8dDd6ylkbObLTRw3oNb0GMzbssckhHxGOv+Nlo+h\na6RtgzDkbS8S8QVKQ1YeGIaGEX395WziWjK0sb1qmgxOXe514n/PKz13I+j2mdz5ViSqr3TOausI\nXHZkFS/ts4wvrO2viZ/rHJMRV3jUIudnttQkrvCMHaNSzUlsfqbYjP6U2aO9R2Yo1hyOnS3RcgNm\nSk3+89OHmSk1mZxv8OT3jjM532DDqhxz5RZ/9swxSjWH//bMMU5dqDAxX+fcTI1PfGAzumlw1y3D\nDOZTzBSbHDw9zwduX4Oma9SjPfy2jUMUsha2ZbB+NMdbZ4uMDaaZmK/z4J3rMXSNct3FNnXmyk0O\nnyny0F3rMQydWtMlZRm8enSW9aty5NImw4U0xy+U2bImz9GzJXZvHSYwDH705iSZlIlhaAzlUxSy\nNvWWFJ3YMJZjekHu2X4gB9YXsha6BvmszYnzZcaGMkwtNNixcRBT1xmfrrJ+LMv+Y/Ps3jLM5EKD\nzWvynJ+psWEsT9PxGczbpCyD05NVtqzN9/RM7ixfF2E7C5nYjdNuo4gFaaStuJFdRVUcDS+xsfmK\ndJbmooqOt84UGS6kqDZk71q16fHvv3aAkxOVqC2jybOvnufCXJ0/+tYRLszJMuRfenQX3917ji1r\nC7znlmHePLXAHbeM8M094wzlU3x333nu3DbChbk69+1czYtvTLBt/QDHzpXYsWGQ87N1dm4e5vj5\nEj/z4Db2HJrijm0j+H7IcN4mc65Es+EylEtRqTu4QUjL9dm+YQDT0Hlu/wXWj+b4wZuT3L9zjHor\n4O7to7w1XuI9twxz8NQCt20cpNqUwbKxoTReEHL75iEcV9B0PQ6fKXLbpmEm52usGclhGjpnp6ts\nWZOnWHPYtn6QN8dLjGRNDp1e4J6dY3ieoFx3GMjazBSbrBpKM5C1SUVO5WDOptb0yKYtLENjttRi\ndDCN4wbkM5bM6mkws9Bg4+o8jhuQS1voOlTqHtm0SSBCUpZB05XJjkZLvt6NZkkOUa1WI5/PJ58b\nhoEQAl3XqdVqicED5HI5qtXq5V7m2rkoWgrt2TAAHX5Su8mzI0oF7cuq27FZz1ecRV8zFx2+0N64\n600P09CTC8mx8+WkCfRv9p6nWGkRdgxLzGWkPv5suclCzaHpBARC/tLVWx5npipMp0zmyy00XcML\nBNWGS7HuQig39GKlRSZl0nIDDp8tMl9pMVNqRkNBBTPFJpmUQanq8sqRGQoZi0bLR4+iZbZpYFs6\nYVRnPVduYZk6h89I5Z5qw5U/kx9wYqKCEPJAb7R8zs81MAwNmEGEIZWay/GJSpJh0ID9J+YJRMjB\n8RKGrslZKZEKzCtHZtE0eekIRIiha4RhiK7ryfskLy0hht6+fPqBuOQyaho6d9y25opmsVx2ePFm\nfHH0Pn7g4jpnPxAsVFv4QUg+Yy1Sp3Oiy9E394wn71G1IR+rNqRCTqnu8n//9zfkLK7oeyfmG4lT\nP11s8ufPnKBUcyjXXMIQynWPmWJdqu+IkFLNQYiQ//bMcWzLoOUGuF7AmckK5brL+dkalqnzjR+c\nYa7UpNb0qEa2RAjHJyoY0b9dpe5yYa6BbmgEgSB1eDrJUnqBIBTy0ucFgtdPzkcXRPm8ECFoYOrS\nMdE0ILITEV8Ww3aflmnqiX2EoSxPCEMwDA0RhJimjh8ILENHAGZ0sY0vvboW2aWQe0F8WQ3DEMuU\nUThN1xLb93yBBliWQRCE6Hr7kvyRezdy546xy9pGt2zw4qt4fOZfHJG/XIQ+tr848l6suYS0975A\nyOxlPHA4LgEFKVBz/EIluTicm63zvf0XmCk2mY/2pT/+9lFyGYtzMzWKNRchBNMLTeotnz995gST\nc1INTOyf4Ox0hSCUF5XTk1VStsn+E/N4geDEREU6ttFeLkTIQtWh3nApN6WjE0dLhRDSDpH2EO8V\ngQjRkI5QGIbYliGNK5Lobf+Kyr1H2qNOEAi0yGbi3z/5+vISFduPhgzOXM7Z8kW46L2LX8s09Mi2\npZPnRyqBiUOOhmFo0Z4ZYhjy98APpHSBrumJkIH83QNdh3/4c3deMWOxnGfyov0vKevoeL7ja5Og\nUmynF5Uhy4/ln53vZWe/MLT7NTsfC0Tbxt1gsaMVO02VhofjyYvvhbk6rejCXKy6+EHIQtJTIr9+\nptgiECEX5uoUqw4/PDxNyjY4PVHBNDT8QFBteJyeqqJpGq4nOHm+TKXhMVRIRfvMLC0nQNfles7N\n1tF1PdmbgkBQrDpMFpsyIxDK/sCG43FisoqhR4NIRcgrR2YQAg6NF9E0TWaDIxszdLm/BiKk0fJ5\n61wJPxAcOV+SjwfydyeM3v9QmiO+Lzg8XgQtGmlyRH7/yakKOhr7T8wRAvtPLrT36lDuo3PVYbZv\nXXVF2+i2HV505CazA2OSqo6L9sv47O3sQUpK3+OKD79d+VGN7KfpytK7WKyh0pBZzNjBqkQO+0yp\nyX9//iRTC3Vmyi0OjRepNz1eOTJLqdrCMHSajs+JaOzBvqOzLFQcDKNGvelxZrpGqdpCO6cxW2rw\n7P4LnJ2sUGv52JaR7B2p+OPIPoQIOXquTCBCpubrnJqocm5G9t3pmsaF+TqOE3B6qkqjJe02RAYa\n0ikT2zR4a7xESBiVk7qcnq4hgpBUqkwYguP5HLsgq6VePTaX7MGuJzg5VcU09CTgk+xnWryniSRo\nqWlte43vjbqmRf+WYfI4RIGqyIYNXSMklCIa0fc8cOc6fvyuDe/Idq6FJTlE+Xyeer2efB4bPECh\nUFj0XL1eZ3BwcOkrDOUvdSDkIRgbbRwhdj1BytITByZlG/hNn2zKpNrwyGcsilWHobzNQkV6qzIV\navDo+zbx5LMnGMhZzJYC7t4xxsnzJc7N1Fi/KsfEXJ1t6wfwffkLEgQh/+in38N3957DMHQee/hW\nPD/ANHQqDZejZ0tROl/j9i0ykn5hrs5ffO8E7711lMNnivzCI9spZCzOTFbYtmGQlKVTqrlsGJOb\niJ2xcZtvPz+p5frMFpvMlJrct3P1oufii2dshEtNv46NFZidvU5Htst02w6je1XyZ9o2aDoBhqHh\nB/Ji7Xoici4FpqnheiGp6OvWr8rhegH/4hfv5fefPoQIQo5fKJOxDbIpi0rD5f/65Q/yB0+/RbHm\nMJxP8capeW7bNMT4VJUdGwf5+5/ajQhD/ss332LP4Wl+7qFtaMBLB6e4f+cYH757A9WGyzf3jLN7\nyzCb1xRYqDrMV1rcvX0V3/7RWTavLVxS5tR0fDIpk+PnSgwVbMaGsouyM/3y798P63i7iGi3bFDX\n5KEe255t6rTcILHBtK3TdAS5tEml4ZG2jSQrnrINGi2f1VE0+Mfes4bn9k+Qz5gsVBwKWYvdW0eY\nmKszNpTh7u2j/Mm3j+IHIbesK/AvfvFe/sNfvsGR8SL33TbGox/YjBAh33jxFPWmzxce3QnAkd2r\nGcqnqDY9HDfg1g2DZFImtZbH+ZkaOzcNUaw6jAyk3/F7HtMv//69XgPwtuVby7UXAomjahoaIlJ/\n1XUtUeM0dC0JMlrR3miZBo4XkLYMGo6PbeqJ82IZOo4IyGUtSlV59qVTBvWmTz5jUa65jAymmF6Q\nl9J82qJcd8mlTUYG0pybqTEUZW9GB1JMzDfYvWWYAyfn2b5xAN8POXGhxN/5+G18//UJDp1e4EN3\nrmP/sVl2bR7mR4en+dB71/HNPeP81Ac38+KBCf72x27j8Jkin3pgK+vXDb7tv/90scFIIXXV7Pf1\n0i92+HZ02w6N5C6o4QUhlmksyhLFd0HL0HFFQCqyt0LGYqHqtD/P2piOT6Uhs2gLFYfhgrShNcMZ\nVg1lOH6uxOqhDPWWz+OPbOeP/+YIuzYPcWaqyu6tI7x6dIaH7lrPyweneOzhW/mx96zFcQNS9mI7\ncFx5Z/jdpw7xuUd2cOj0PA+8dx1Pv3yG27cO8/0Dkzxyz3pOTlS4Z8cYb5yc55F7NzBXbjEykEoC\ng1f794/veq8dm+U9t4wkqrg3mn6ww7c7k6+HJTlE9957L8899xyf+MQneP3119m5c2fy3LZt2xgf\nH6dcLpPJZNi7dy9PPPHEO3r9RZtvVOoSiBBT1/CQWYq0bcheIk+W0cQO0UDWRgRh4hAN5ezIIUrh\n+oLRgTRz5RZb1xb40J3r+KuXz7BmOMtsSZYA3bImz7P7z/PIvRtkydLGIcp1h7GhLGtGMowMpPn5\nR7YninjxJjiYS/H+2y/NZmzfMMS/+sL9hGHIT75/c2Kkq4Yyydd01p4O5lPMXsUhStsmm9YU2LTm\nUqO42Pm5mWtRu22HuqYRRBGJIIwzWgGGruMH0abryfIt1xfYpoHrCbIpi6YTsGFVjr/3U7cD4Psh\nd29fJeuYXZ9AwO6tIxSyNr/y2bsA2HNoCgH87Y/u4BsvnuaTP7YlWccvPbqLD9y+Julb++B71ibr\nLGRtfuGRHcnng/kUt6wbAOCTD2y97M8W9x7t2DTU/nl1DZ2b1166QbdsUIs2QRlRDjscIjNyiEyZ\necxaOJ4gZRsEIqTlBuTTFkEQsm40i+MFPHzPBl55a4bhfIqFigwO7dg4iOsF/JOfey8iDHnqpTPM\nlVvcumGQlGXw0fdt5sxkhfffLgMuuq7xtz5866I17toyAsDai9aeT1vs2jwMcF3OkOLa6eZeqNHe\nC0FeSg1Di4Ju7chu7ASZhtwf46/DB9vScbyAbFr2ZKRsE8eT51zKls8N5VJUai4ihGzKjBwim3LN\nZdVARoqFOAGFrHSIhgspxobSXJitsXVNgZlik11bhpkpNXn4ng34geDH3rOWW9YVODNZY/eWEQay\nFptX53n0g1v4+P0bqTQ8fCH42YduQdPgJ+7dyCP3bsDQdXZGNnw11gxnr/m9vNnp3n4o74SxQ2Rb\nBiGBzKahJQ5RvD+mbOlEWJYODqwaTFOsOmQi+8umTVKWQaXhsXFVHs8XjA6mqdRdfuGR7Rw+U2S+\n3GTDqjwN1+e+nasxDJ3RQopXjszwkXvWs340x0/ct5Gf+uCW5Dy92BnqfOyf/Ox7AXjobpnZ+JkH\ntwGwc5O0s1s3yLP4J+7bCMBYxx3xWojvevfedvlqBsXVWZJD9LGPfYyXXnqJxx9/HIAvf/nLPP30\n0zQaDT772c/yxS9+kSeeeAIhBI899hirV6++yitKokzgos3XtqImM006RxBgWwaWZWAaIbWmt8gI\nhwspufFGBrp13QCnp6oUsrLe8JF7N3B2psqH7lxPNm0xmLN5/+2rOTNV5f13rCWtwYN3rUeEMlo6\nNpTF84NF9YpLETLQNK1rHvtKpVt2aEYZIC068HUNAqQTUWt6mIaG47X7TdK2Qa3pJWWFAzmLYlVm\nIWN+7fG7AZmZOXa+xK89fs8lf+8H37OWTz+8g9nZKn/3E7suWtPlRTwUvaVre2G0xRiaRkBIJi1t\nL2MbFIFc2sT1ZK11y5WRdyFkr9FQ3sYLBBvGcpTrLquHMqwaTDOUT3FyosJgLsWP37GO0chZkf2G\nKekQrZcR249+YAuTs1Xl0LxL6JYdAmi6luyBEJ/DoSx/ReBBFCzq7MMLoh4tHUMPsEwD0/CTi2Mm\nZVCJkgXZlEml7jGQs8imLWnn0dcN5m0uzMLIQIrZkk3TaTKUT8le3EKKsaEMA7kUt24Y5NCZBX7m\nwW0M5mx2bx1h99aR5Ge4e4e0441jBTZG0eWhQpqhQponPrkboMPhV0GhpdL1u2F06TcNXTrihk5I\nu5wykzIpVh2yKYsgcElFAevVwxkm5utkUybzQD5jkbIMSjWHO7aNsFBtMZJPkdo8xN07xmg6AZML\nDbauK+D48i5693ZZKhgHoj/2vk3J36m4OVjSv6Smafzmb/7mosduuaWtnvaRj3yEj3zkI0t4YSBs\nXwZA9hz4ocAwdOKWE8vUSXWoZsWOhmXqjBTSlGtuchl98K51vHFyjuFCmn/yc3ciREjTDXjgDhnX\nHB1Mc89tY8yWWmxa3U4F6prG+lX55HUV/Ue37LDTEQJkyj+QogBA1GMlnXWQ5R3Q3ozzGZtMyuQj\n92686DXho/dvXFQ/r3h307W9MCJlt7OPhqEnGels2qLe8knbBkM5u0MIxKKQs6m1fG7fMsLZ6Rqa\npvFrj9/N0bMl3hpfYDCfImUb3LW93QsQZ8nv3iEfM3SNT/7Y1iWvW7G8dNMODU329HlRn47suYr6\n+Vi8J8bPg7y0GoaGaRjYpgwIxudyxjaTS24ubQFN8hk7CS4NZGXVxIaxPIdPLzCQsxnIWcyUmtyx\nbYSDpxcYHUxz6/pBTpwvc//tq3n12Cz5jMWnb5CSq+Kd0727oUwRxbZlGBopjMQWY3c97hHKpU2a\nrp8Ey0cH0gzkUgzkZGB7IGeTS1usGcnyvl2r2Xd0ll1bhhN14g+8Zw07twwxUkj3RYmYYnnoK9e2\nXaMsU+4ga+ljKUIz8ohMQydlm8kvR1xbnbIMxoYzzJWbpGyTXNpkzXCW924bZWdUGqTrGg/dtT75\nO//nx+5C1zV+9qFty/VjKt4lJFF6QwNP9q0BSU2vZcjP7eiSmktLO8ymTOotn7Ujl5ZSZNNWkipX\nKK5E7JTHWUjL1DB1LSkFuWXdAOW6S9qWamu+LzB0jYF8imzKJJsy2LFxkNVDO6PvN7hj2yg7Nw0z\nXLhUHva+28YYGUirLLbiUjQNjcUOTxjKYGXcvN4piGNGAURD1zB1HdOQPUS2JZJoeto2sCJhlHxG\nXlIztpE8v3Y0y8HTC2xZN0DGNhgppBjKpxjIWrxv1xqe+sFpVg9lufe2MfJZi+F8in/5i5dm3RU3\nB7Jssx1YTFkGLeGjGxpm2LbNtaNZphYa5LN2tD/K/SyfscimTAZzKUC2Vrx32ygLFYfByHY6VSB1\nTWOkoLLjK42+Sn3EDk7YEUHPpExMQ5P9DdHzlqmTsnSyKRNDh8GcPOBTliH7NAJBJmWQy1hkUiZf\neHRXMkvjYm7mHhvF0oj3xbjpN57fYiaRz+hPM8oURReAXHSwW6bO//urH1629SpuHn7x4zujg19+\nrusaZlx6ZOhRNF0637apk7YNBnI22bRJPmOzdU0B29TJRDOphgqpRa9/2+bBpL+nkzu3r+KnP6Qi\n64pL0aL/xUdlkvkx27LlRsc5mmTS9ehrDA3bkmd27HCnU9IhskyDbDp2kmQQM2UZ7NwsA5g7twyT\nTVts3zjIqsEMa0ayDBdSjA6kuW/XKnRdS+y5m7Lmit6iaVGPa3RjtU2DwbxU9bM6nPGRQgpd18im\nTaxofwTYsrZAyjb4yL0bIlnzFLu2DPOPf/aO6PWV7Sj6zSFKLprtZel6XIesJVEo29SxLYNM2sAy\ndNYMy+azTMpg0+o8/+rz95NNmQxkb7xOueLm5bboEI57xOKDWovMMR+VcbTtUG62A5FDnkuZmKaG\n1XHwKxTvhM/95C4pJBN9Hu97lqljGVpSApLPmFiGPPBXDcj+oHTK4IE71iTZ8cvxsfs3L+qtUCiu\nhh9I+fH4ziht0UjOZVjsEMUXVCkNrWMaOrapk7LMZF/MpixMU8e29CSQlE4ZMpKfNtmxYYh8xmLd\naI41wxnWr8rx8D3refhuWd3xL//2vYwNKjGDlYKmSec7PptTtrQ96XRLe8vYBvfvWk3GlnZkm9Gf\nls6qoQy/+gt3c+v6QWzLYNeWaxPMUKws+qpkLt5SO0UL5EBHPZriG/8yGNiGTj5tYRg661flSVn6\noua2XMZKLqoKxbUQ6+TH9hcf8vHn60azHDjRfjwTXU43rMoBUMjZZG0zyRgpFEsljljqyMi8ZcgM\nUXzZHCqk5T5oyV6gs9NVfuyOtZiGTu7UAq6v9j7FjSEkjPZGWcZpm3L8hWFoGEHcT9kOAJmJQyTP\nbMuQDlQ61e67zKRkMFNoYVIyl7ZNCjmbQtaikLUYzNsM5Gz++S/chaHrrB7OsjpSdOvGUEZF/yId\n8vbg44xtMl9pYRntx7xAcOv6QdK2QT5tYplaYk+dd8FH7t3AxrH85f4axQqnL29uWkdqPpeWaiCy\nOTNqYrcMbFtGlgxdZ9PqHJmUtUjVazBnM5hPXe7lFYrL0mh5i0Q99I7op2lo7I6iSkZkh4W83GQ3\nrs5j6LIuPpM233ZeiEJxNTqj8ZquRcEgXV4wI2d71WCadMogbRlsWVvgwbvWJ/vj9o2DycVRobge\ntOg/Xe8QSzB1NL3tpAOLzl5zUYZI2q5tyWymnWSIZEmTFZW+g1SSG8qlGCmk0TSNz3/8tigz0JfX\nFMVyorEoQxRCojIXC808fM8G2U5hyzPYNHSGcikGsvaiILsSi1FciT67uUmjTS6kmswQ5SPHJ87K\np1MGhayN5wlsW2cgZ5PPmEmkCaQWu5KMVbwTdmwaZmK2ngy4jHuHDEOWfRSyNqbZzlSuHsqQsnTW\njmSlFLyhk0uZyQGvUCyVuIldj6KiescE77h/MpeyLjv3YsfGIXZsHLrkcYXinaLrGmnbQNfa/UJm\ndAk1jMVVGzEpKxYCkSVzlik/Nk09yaoXsja2aSBCwWAUWFo9lGEgayevedsmVdakiJ1yLWqfkLZx\n6/pBLEOnXHcS24sltrMpg0zKQNc13nPLMF97/kSvlq54l9FXoZckKtoh5TmYk2lzQ29H5qV8p8n7\nd68hZRrk0hYjA2mGO1RBBvOpRbKyCsXV+Ps/fcci+dgk0hltxPmMhaW3y5Y2ry5gmYZU57LlBmwY\nOl4gLvv6CsW10qlwGDcUl2pOlCmSPZT2RWXCCsWNRo/KiKVTLve9bMqMmtmN5ILa2TMZ26ScPSSd\nJts0yKZMMmkpt71t/UDSC7xhNE82ZTIykObWDYN84oNblv3nVPQnu28ZiewvylTGfeaGxmc+tBXL\nNIXoUKUAACAASURBVEhZMlgej7+4Zd0AwwUpuLBpdYGv/i9K4EhxbfSVQ9RyY6ntSE3O0LkwVydj\ntxs4symTtaM5Pv3AVjatzicKdJtW59m9VUWUFEtHA3xfMBSVWsbOkRE1tWfTJoahMzKQxjJ1xobS\nZFIGKcsglzIZHUhTqjncs0M54orroENe1tD1RHL2d37loUSZS0ZFNYbzqldI0T1iQZkwbJfMpVNG\nNCi9rfBlW20hkLhSwzS0JJuUtqWa3OqhLIN5m81rCtiWdIhGh9Lks5Zy7hWX8JkHb036enVNa1dt\n6NLZsSJn29D1pFT9cx+9jVWDmUUS3QrFtdAXO9C6VTkm5+rJ53HJsIyKujI9H6nNDeRsPv3A1uRr\nt64bADqnTCsUS8PzBSJsy8t2KijpmhbNzpBOuWloDBfSFKuO/BpD2uY//tn3Xnb+kELxTtA6bFCP\nlLp0XSNtGaRsHV3T2LI2zwbVHKzoInEzuwjbg6ptU5czA8P2qIG0Zcrhrb5geEAGlExDjy6yoeyv\nTJls3zDAutGcdJQsA0J5YV0/muvND6joa27bPJyIHdExjuDsTA2QYh62qaPrMDaUSb5vMG8TCFWp\noXhn9IVDdLECfFwyZ5o6H9y9BtuScw8MXaOQWawu80uP7lqmVSpudvxAzr8S0Ryszpr5dMpA0zRS\npkE+a5G2TTIpoy1hHMKa4YwS8lBcN537oaFrshejo1E9VjF84I51PVidYiURR9lzaZOWK3srs2kr\nskktib7blo6pa3jA2KC8mNqmDpqGEIJc1mLtcJZs2uLXHr8bkOJIsbH/07/13uX9wRTvCox4BuVF\nCrAfjuTXLVPHjnrcRjpmrqVtkw/sXtOTNSvevfSFQ3QxjidL5yxd59EPbGbfkZlo4rWW1IkqFDca\nK7poNuPSzShV6XhBMnNI1zWG8ylSlnSQfuXn7wJkpDSXUVKwihuB1u6n1MDQwTLbfZWxLSoU3Sbu\n3YB2oNI2dZquTz5jkY9m/UklWB3TFKwazEi57Wg/DQ2Dj963qeM1o9I720g+VoMxFZcjrs7QdA0N\nLQmMx3ugECFpy8DsGMIa8+Cd63uxZMW7mL7qISpEm2u8yeq6xuY1BRmNMmWkQNWDKrrFUBRhigf6\nxgOwhwqpRZKzIwMpGo6/6Hv/18/dk4gwKBTXgxeIRSpzuiZL5UBePGM5eIViuYhL50D2tQkRslB1\nGI4y4mlbqs5lbZORgVSUyTRkBP8K+2I2bSXDrxWKyxHvdbGwgq5Loa0NY7LEcjCfShRe06oHTXGd\n9IUFtWW2I+OPLwMdvUTxtHaFopuMDsoZGLKRvS3uEUefdE0jl7bwlZKcoktsWzfAXLkJyDlEImwP\nvpRSxsohUiwPiaV1yG5bps6XnvgAQoQ8v/9C8phlSrWvbNqUUXxLT8qPL0fsOCkUVyKeyaYTDWaN\nskRmh5hHrelJSXdVPaS4TvrCIbqYdkNxe55BLDeroqOKbtJyfHIZK2rilI6RZepU6tIBMnSNbNrk\nd37loZ6uU3HzsmYkw3y5BUiBj1za5PysbCJO22YynFWh6D5a8n+jQ/IYiMYMtJ0kKxqkbpuyhMmK\nxBeudGI/fM+Gbi9ecTMQSmfIMOR/QrSd7IWKw0DOxo5mXikU10NfWNDFqc4kYxTLfNoGZtRcnFL1\n84ouUm/5LFRacu5GlKI3ojQ9SNuM5T0Vim6gdfYQoeF4AffsGAMgnzFVhkix7IS0M+Z2h0MeV21k\nUiaWqTNUSKHrUo7bsgxsy7js8GBol4MqFFck6TGL7AXYtKaQPH38fIl7bxu7oo0pFO+EvrjZffie\njZw8X77EEYoP/lxKRuwt08C21Aaq6B6xvHsgRNTMKUvmAlNGpWZLLZWaV3SdxCGKRg8MRfOG8lmb\nK8fcFYobTCx3TLuE3ewISsY9vbmUiWnobF0rL6umIccUaCGqqkOxZBJBD11LhgOnOhzyf/MPHwDA\n81QJu+L66QuHaOPqxbM0puYbQHtQ62BeXgIsU08GcykU3cC2DFYNpplaaKBHyjaWqTMb9XT8/+y9\neZikZXX3/3lq7erqZXp6ehaWGXZGZHPAaFQgEkUMxCTIMAM4mIQk7y+Jvl5CfEW9koASGY1i3jco\nCgmiiCEgKKIgYZVNhlmYGWbfeqZn6b27uvZnvX9/PEtVz85MVz/F1PlcSk9VV1edqv72/dzn3Gc5\nc/YU4nJKKdSSqiVO0yBfMoN5Q01x97RcECYDDSjrNh0tkaDJTKoqGu//O52KU9Yt3nOGO5Q6EYuS\nSkSZPqVZan+Fo8MbyOo75fp+nJ//9Sfvnny7hGOOunCI/AUzkzcAMCxX8P5xekvKLWLXDYuOThl6\nKdSOkm65J0MQpM1Fo1owbPX/+5OzwzVQaAj8jl4RDd5z+jTSTV57Y6+blyBMCprX9VAjmIWViFcc\nHD/dvSkZIxqNMLPDXSe1iMa0thRz53RMvs3CMYO7DCo3OOmlsE+b0rTP42bJYF9hAqjL0I2fHpLJ\n64Cbn7ytN4tuOjRLa0WhxuimTTSiecXDGkOZMpmcHrZZQoNQ7e4UyxaqqlNXIhbhhK6WfX9IEGpA\ntRb92qHqOVhNiag7cyga4S8+Pjdw5GMRja6O1GSaKhyDKOUOTHfnEXmDqqUzoVAj6sK78LuDTGtv\nYmisTGtzgkze4IwTpwBur/kr3j+Hj1x44sGeRhAmhNFcmWg0EjhFsVhEHCJhUvEzgztak8E66N6v\nceUHTgrHKKFhePcpnazdNuyXEHn1G16To6oaypg3ayiZiHJSW1twfzwWDQKbgnCkWLaDabn1vGgQ\ni0o3OaF21IWyzj61c9yU4co8ogriDAmTxeknTPHazLpt3qdPSdE3UgzbLKFBcDehlcGsl5wv7YmF\nyeWCudMBUGjeqY8iEol4zRIqcdR41G23vffA9IvOnSW1lsJR09qcoLU5TiTidiS0bIdYTFKGhdpQ\nFw6RplXazII7dwPgjQ0DIVkkNDLZouHVD7nb0is/cBLf/swHwzZLaBT8sDyVWiJBCANNczM3BjPl\nIDUuVZW2nohXZgRW8/tnz5xsU4VjEN8Ringpcy2phIwdEGpGXThEPv61XwYPCmGRTsWY2tbkFXBW\nBsLJvAxhMvHVpg76KEGoLbmiCRoc35VmJFsmFouQrGqqkIxLkw+htuRLJprmNuqIx7R9nG9BmCje\ndg1RuVzmC1/4AiMjI6TTaRYvXszUqVPHPeb2229nxYoVpNNpNE3je9/7Hi0th18IfPoJ7SilmNEh\nHeWE/VMrHRZKlpsup2ls7815xZxywRf2pVYarD4VkmCocChqeU3WAOW4X1OJmFtTWbUhdessZYMq\n1E6HtqOIeMOwopEIli0zh4Ta8LYdov/6r//izDPP5DOf+QxPPvkkd999N1/5ylfGPWbdunXcd999\nTJky5QDPsn/8vPloJMLnrzn/7ZomNBC11GFHa5JuDd41p4M3Nw9NpNnCMURN10JxhITDpJY6RHML\n2zUNIt5JebXDrmnauPpfoXGptQ41DWzH4cTprRNotSBUeNuhnRUrVnDxxRcDcNFFF/G73/1u3Pcd\nx2HHjh384z/+I9deey2PPvroYT3v7581k4GMO/xSoqLCoaiVDgHvog9apDKdXRD2plYafHPzULDp\nFMdIOBS1XgtbUjFAY+vu7H5r2qqbLAiNS611GNE0MnmDtub4hNotCD4HXckeeeQRfvzjH4+7r7Oz\nk3TaHYKVTqfJ5XLjvl8qlVi0aBF/8Rd/gWVZ3HDDDZx99tmceeaZBzVke1/leaSQWKhmMnV48qw2\n1xkKmiqIFoXJ1WC17kR/QjWTqUNwU+Lw1sKWVGxcQwWf6TJvqOGYbB36NURbd49JiqZQMw7qEM2f\nP5/58+ePu++zn/0shUIBgEKhQFvV7AGAVCrFokWLSCaTJJNJ3v/+97Nhw4ZDir5/tBT8u6U1SVdX\nOMeiYb1uvdkA9WPHZOqwuzfLeadPIxaNkG5OEo9FJv1zqJfPXeyoMJkavPTCE1m2oR+A5uZEQ6+F\nUB921IMNMHk69GcBO0oRj0cZyZX5k4tP47llPft8Fv+w6L0T8M4OTD189vVgA9SPHZO5HgIkEjGi\nUY0Hbvv4xL2Jt0G9fO5iR21522fd8+bN46WXXuLcc8/lpZde4sILLxz3/e7ubm666SZ+/vOfY9s2\ny5cv56qrrjrk855/eievvtUHQKGgMziYO8RPTDxdXa2hvG692VBvduyPWukQoFy2cJRCL5s4Sk3q\n51BPn7vYUbFhf9RKg6WSgeMVDg+NFht2LawXO+rBBt+O/VELHVYnaZiGzfQpKZ5ZsoMd/bmGWw/r\nwYZ6s2N/1PKabNsOykHWQrEjsKEWvG2H6Nprr+WLX/wi1113HYlEgm9/+9sA3H///cyePZtLL72U\nP/3TP2XBggXEYjGuuuoqTj311EM+b3u6MtU6ImkiwiGolQ7n/8Gp5EomGlowA0EQ9ketNIhWSRue\n1t5Uy7cgHAPUTIcee4YLTG1r4sPzjuf+pzbU6m0I73BqqcOI5s4kEoRaoiml6mLUxd2PvMkzy3Zh\nWg43fOxM/uA9kz+dvV4837BtqDc7JpPBwRw/e2ELyzcN8r6zZrBi0yBfvfF9k/b69fS5ix0VGyaT\n7z38Jmu3j9DTn+eK35/DJy85/M3rRFEPn3u92FEPNvh2TBaPPLeJHz+53tuIRjj7lKn870+eS3dv\nlpNntR36CSaIevjs68GGerNjMvnjmx/n3FM7iUU1PnPVuZP62lBfn7vYUbGhFtRRdZrGCV1uQV5C\nBrMKYeK3+LSVnBAJk45G1QgCGXophIijoCUVC3I2JtMZEgSA46elUci1WKg9deZ5uIKPx+vMLKGh\niGgajoJUk0xhF8LBb/cumwAhbKZ3NEsSuxAambyOUtJ9WKg9deN5bO/NBvOHZBMghInpFbT7sw8E\nYbKJBHOIRH9CuGjBfwRh8pkxtZlUIioz2YSaUz8OUX8OxytnWrFpMGRrhEZmrGDQlIiiQDYCwuRT\nVUBcNwu00LhoEqQUwiWiadJUQag5dXO91ahsAj54zqxwjREamlmdaTQ0dMOWwZhCCGiVkyGRnxAy\nO/vzSHheCA3lDmUVBQq15m233a4VhbLF1t1ZANqaE4d4tCDUDtc5h1RTjJjUEAkhEI1IypxQH5i2\nQ7RuQqdCo1EyLKKaJsEhoebU5TKXkKYKQohoXoqI4yg5phcmHU2rBOQlVUkIiz//+FymtiVJxiPE\nxCMSQiLdFMewbAkOCTWn7lY5t4BThC+ER0TT0DRoaYpTH1O6hIZCVdKH5YRSCIs5M1pJxqM0J+My\nLF0Ijf7RIpat6m+zKhxz1E3KnI+m4R6PCkJIuJtRjUzeIFswwjZHaDC0qiL2mMxkE0Kkd7hIPBqR\nGKUQGrmiSVtayiiE2lM3V9uOliTvPqmDiKbJJkAIFU1zCzjnzGyhJRUP2xyh4ai0e49KyqYQMqbt\nSP2GECrVTbcEoVbUj+ehga3AQTLmhJBRCi3iNvcQLQqTjaYRDAQWh0gIC3/te+/c6VK/IYSKpmmS\nOSTUnPpxiADbdlBKSSGxECp+i8/BTIlMXlLmhElGg1hEHCIhPKZNSRH1GilEIhU9CkIYaJqcEAm1\np24cIk2DkWwZpaBsWGGbIzQw2/tymLZi9oxWbEe6KgiTSzSiBZvRkm6HbI3QiHz4ghOZ2poEYM22\nEXYPFUK2SGhUzjllKpGIDGYVak/dOERjeYMzTpwCQFxafAohMquzmXRTnEQ8ymCmFLY5QoPhOkTu\nxb8tLTVsQjjEvVred83p4JRZbSFbIzQqhbJFRNPqZ7MqHLPUjcZsR6EUNCdj0lFECJUp6QQRDTq8\nCKkgTCYRTSMWcZfmGR3NIVsjNCr+7KENPRkp7BVCY9ueLBENIpG62a4Kxyh1o7Abr3gXyXiEom5J\nAacQKnuGim5nJeA/v/jhkK0RGhE3RYQgdU4QwsJ2HCRbSQiL9797BiXDRvwhodbUjcRamxO81T0S\nthmCwM6BHIbpOkTinAuTjRZx0+b8AcGCEC6arINCaMQiEVpTCWkwI9ScunGIyobFSFYP2wxB4MQZ\nrfSNFMM2Q2hQNNwaIqWQjptC6JxyXBvrd4yGbYbQoExpSaBFVFBXKQi1om4cotVbh8M2QRAAuPDM\nLk49XoqIhfCIRyPYjpITIiF02lJxtvVmwzZDaFCuuuRU77RcFkOhttSNQ9TTnwvbBEEAIBGLgnTb\nFkLEbzEbj0VDtkRodI6fnqY5GQvbDKGBiWgROS0Xak7drHKjOUmXE+oDOZoXwmRorEzM02AiVjcx\nK6FB0TSN33/3zLDNEBqYSETqeYXaUzdX2xO6WsI2QRAAKJYtxopG2GYIDcpzy3eRK7j6i4tDJITM\nIy9slQ5fQqgk4lGKZTNsM4RjnLpZ5tKpGB9/3+ywzRAEZkxtlgYfQqjYys3ZjEnbbSFE/JPKp9/Y\nGbIlQiPj2IpZnemwzRCOcermatueTpJqqpsMPqGBiUU1sgU5IRLC4bqPnk5TXNZCIXz8VLkTp0sG\nhxAeb3UPY1h22GYIxzhH7BA988wz3Hzzzfv93sMPP8wnP/lJFixYwIsvvnhYz3f9R8/g8t+bzXHT\nZDK7cPhMtA5B0pSEt89E6vCckztpb0kwZ2brBFspHMvUYi3UNDj75Klc9t4TJ8hK4VinFjo8blpa\nGh0JNeeIwpC33347r776KmedddY+3xscHOSBBx7gscceQ9d1rr32Wj7wgQ+QSCQO+pyRiEYEjc9+\n8twjMUloQGqhQ4BoJMJ9t1xaC5OFY5CJ1mE6Feeskzo45Thp/S4cHrVaC6/9wzMYzpYlOi8cFrXS\n4UcuOAHLdmphsiAEHFEofN68edx6660ota/Lvnr1aubNm0c8HqelpYU5c+awcePGw37uGR1yQiQc\nHrXUoSAcLhOtw5ZUnDNO7ODcU6fVymThGKNWa2EyEeW4aWlOminOuXBoaqXD6R3NHDdN0jaF2nLQ\nE6JHHnmEH//4x+Puu+OOO/ijP/ojlixZst+fKRQKtLZWUj3S6TT5fH4CTBUaFdGhUA+IDoWwEQ0K\n9YDoUDgWOahDNH/+fObPn/+2nrClpYVCoRDcLhQKtLUdOrrU1VUf+fL1YEc92AD1Y0ej6bAebACx\nY28mS4f18n7FjvqyARpvLYT6sKMebID6saPRdFgPNoDYUWsmvHr83HPPZdmyZRiGQS6XY+vWrZx+\n+ukT/TKCcFBEh0I9IDoUwkY0KNQDokOh3jni3q6apo2bHHz//fcze/ZsLr30Um644Qauu+46HMfh\npptuOqyiOUE4EkSHQj0gOhTCRjQo1AOiQ+Gdiqb2V/0mCIIgCIIgCILQAMjAFUEQBEEQBEEQGhZx\niARBEARBEARBaFjEIRIEQRAEQRAEoWERh0gQBEEQBEEQhIal5g6R4zj80z/9EwsXLmTRokX09PTU\n+iUBWLVqFYsWLQpuP/PMM9x8883B7WXLlnHNNdewYMECvvWtb03465umyRe+8AWuv/565s+fz/PP\nP8/69eu5/vrrWbRoETfeeCPDw8MA/Pa3v2XBggUsWLCA22+/fcJssG2bL33pS1x77bVcd911bN68\nOfjeE088wcKFC4PbDz/8MJ/85CdZsGABL7744oTZUM3w8DCXXHIJ3d3drFu3josuuohFixaxaNEi\nnnrqKQAefPBBrr76aubPnx/cNxGEoUPRoEs96bDRNAiiQx/RoUsj6lA0uH/C0mEjahBEh/sjzLVw\nH1SNefrpp9Utt9yilFJq5cqV6m//9m9r/ZLqnnvuUVdeeaVasGCBUkqpr33ta+ryyy9XN910U/CY\nP/uzP1O7du1SSim1aNEitW7dugm14dFHH1Vf//rXlVJKZTIZdckll6hPfepTav369UoppR566CF1\nxx13qHw+r6688ko1OjqqlFLqBz/4gRoeHp4QG5555hn15S9/WSml1JIlS4LPfu3aterTn/508PkM\nDAyoK6+8UhmGoXK5nLryyiuVrusTYoOPYRjq7/7u79THPvYxtXXrVvXwww+r++67b9xjhoeH1ZVX\nXqksy1L5fF5dcsklE/b6k61D0WCFetFho2lQKdFhNaJDl0bUoWhwX8LUYSNqUCnR4d6EvRbuzRHP\nITpcVqxYwUUXXQTAeeedx1tvvcWiRYuYO3cumzdvprm5mQsvvJBXXnmFbDbLfffdx/DwMF/60peI\nx+M4jsO3v/1tZs6cedivOWfOHO666y7+z//5PwDMmzePj370o/z3f/938Jif/exnRCIRCoUC+Xye\ndDrNkiVLuOeee0gkEvT19bFw4UJef/11NmzYwA033MC1117Ld77zHZYsWYJt21x22WX89V//9X5t\nuPzyy/nYxz4GuNGQWCzGd77zHaZNmwaAZVkkk0nefPNNzjjjDBYvXszOnTuZP38+U6dO5d///d/p\n6elhdHSUTCbD9ddfz9NPP8327dv5xje+wdy5c/nc5z5HoVCgVCrx+c9/ng9+8IPjbPjIRz7Chz/8\nYQB2795Ne3s7o6OjfOc73+HLX/4y//iP/wjA6tWrmTdvHvF4nHg8zpw5c9i4cSMvvvjiUdvg881v\nfpNrr72WH/zgBwCsXbuW7u5unnvuOebMmcOXv/xlpk6dyuOPP04kEmFgYIBkMgkwIZ/FZOtQNFih\nXnTYaBoE0WE1okOXRtShaHBfwtRhI2oQRIf1pMH9UfOUuXw+T0tLS3A7Go1i2zbnnXce999/P4Zh\nkEqluO+++zjttNN44403eO211zj//PP54Q9/yGc/+1lyudzbes3LLruMaDQa3P6jP/qjfR4TiURY\nuXIlf/zHf0xXVxczZswAoL+/n7vuuotbb72Vu+++m3/913/l3nvvDf5onnjiCe68804efPBB2tra\nDmhDc3Mz6XSafD7P5z73OT7/+c8Hol+xYgUPPvggf/7nf87IyAhLlizhC1/4Avfeey8/+tGP2L59\nO5qmkUql+I//+A8uu+wyfvvb3/L973+fv/mbv+HXv/41O3fuJJPJcPfdd3PnnXdiWdZ+7YhGo9xy\nyy38y7/8C1dccQVf+cpXuOWWW2hubg4ek8/naW1tDW77dk+UDY899hhTp07lQx/6UHDfueeeyxe/\n+EV+8pOfcOKJJ3LXXXcFv5cHH3yQhQsX8olPfAJgQuyYbB2KBscTtg4bUYMgOtwb0WFj6lA0OJ6w\nddiIGgTRYTVha3B/1NwhamlpoVAoBLd9r/iss84CoK2tjdNOOy34t2EYzJ8/n5aWFv7qr/6KBx98\ncJyIJ5Lzzz+f559/nne9613cc889aJrG6aefTjQapaWlhRNPPJFYLEZbWxu6rgPwrW99i29961vc\neOONZLPZgz5/b28vn/70p/nTP/1TrrjiCgCefPJJbr31Vu655x46Ojro6Ojg7LPPprOzM4iKrF+/\nHuCAn5Gu65x22mksXLiQm2++mdtuuw11kPm6ixcv5je/+Q1/93d/x6ZNm7j11lu5+eab2bJlC3fc\ncQetra3jfkeFQiH4I5gIGx577DFee+01Fi1axIYNG7jlllu4+OKLg+f+yEc+ErxngOuvv55XXnmF\npUuXsmTJkgmxo1512CgahHB1KBo8OKJD0eGxrkPRYIWwddioGgTRoU/YGtwfNXeI5s2bx0svvQTA\nypUrOfPMM1FKoWnaAX/m2Wef5cILL+T+++/nYx/7GPfee++E2qSU4rrrrguE29zcTCTifhQHs8sw\nDH7zm99w55138uMf/5if//zn9Pb27vexQ0ND/OVf/iVf+MIXuOqqqwB4/PHHefDBB3nggQc44YQT\nAPcXunnzZkZHR7Esi1WrVgW/2Gp792bTpk0UCgV+8IMfcMcdd/C1r31tn8f84he/CI4im5qa6Orq\n4sknn+SBBx7gzjvv5LTTTuNLX/oS55xzDsuWLcMwDHK5HFu3buWMM86YEBsAfvKTn/DAAw/wwAMP\nMHfuXBYvXszf//3fs3r1agB+97vfcfbZZ9Pd3c1nPvMZAGKxGIlEIvi9HK0d9abDRtEg1IcORYP7\nR3QoOmwEHYoGxxO2DhtRgyA6rCZsDe6PmtcQffSjH+XVV18NulZ8/etf55//+Z8P+jPnnHMOX/zi\nF7n77rtxHIcvf/nLR/Ta1SLWNC24rWkaN954I3/9139NIpFg+vTp3H777bz11lv7/Ez1vxOJBO3t\n7VxzzTUkk0k+9KEPMWvWrP2+9ve//31yuRzf/e53+e53v4vjOGzevJnjjz8++OW+733v4zOf+Qw3\n33wzN954I+Ae455++uk8/fTT4+zd+32ddNJJ3HXXXTz11FM4jsPnPve5fWy4/PLLueWWW/jUpz6F\nZVl85StfIZFIAIxbfLq6urjhhhu47rrrcByHm266KXjc0dqwPzRN47bbbuO2224jFosxffp0vvrV\nr5JOp5k7dy4LFixA0zQuvvhi3vve97JkyZKjtiMsHTa6BqE+ddhIGtzbZtGh6LDRdCgaPDiTrcNG\n1CCIDg9GGGvhPjaowzlHEgRBEARBEARBOAaRwayCIAiCIAiCIDQs4hAJgiAIgiAIgtCwiEMkCIIg\nCIIgCELDIg6RIAiCIAiCIAgNizhEgiAIgiAIgiA0LEflEK1atYpFixbtc//zzz/P1VdfzcKFC3nk\nkUeO5iUE4aCIBoV6QHQo1AOiQyFsRIPCO5UjnkN077338stf/pJ0Oj3uftM0Wbx4MY8++ihNTU1c\ne+21XHrppXR2dh61sYJQjWhQqAdEh0I9IDoUwkY0KLyTOeITojlz5nDXXXftMyF269atzJ49m9bW\nVuLxOBdccAFLly49akMFYW9Eg0I9IDoU6gHRoRA2okHhncwRO0SXXXYZ0Wh0n/vz+Tytra3B7XQ6\nTS6XO9KXEYQDIhoU6gHRoVAPiA6FsBENCu9kJrypQmtrK4VCIbhdKBRob28/6M/sHU0QhKPhYTDj\nsAAAIABJREFUSDQIokNhYpG1UKgHRIdC2Mg1WXgncMQ1RAfilFNOYceOHYyNjZFKpVi6dCk33njj\nQX9G0zQGB8OPFnR1tYZuRz3YUG92vF2ORINQHzqsp89d7KjYcCTIWnhs2FEPNvh2HAmiw3e+DfVm\nx9tFrslix0TbUAuO2iHSNA2AX/3qVxSLRa655hpuueUWbrzxRhzH4eqrr2b69OmH/Xz/8N1XOW5a\nmpsWnH+0pgkNwkRrcDSn88Kbu7jq4lNrZbJwDDKROly1ZYiW5ji7BvJccv7xtTRbOMaY6PVw1ZYh\nzjttWq3MFY5BJlqD/3zfGyz8w9N515yOWpksCGiqTs4kfY/z//1sFSu3DHPfLZdOug314vmGbUO9\n2TGZDA7mePCZjbyyuo+7b75kUl8b6utzFzsqNkwmg4M5nnx9BydOb+E7D69q2LWwXuyoBxt8OyYT\n/z3/5eLnQ9Eg1MdnXw821Jsdk8ngYI6/XPw8gKyFYkdgQy2Y8JS5o2XunA5MywnbDKGB6WxromtK\nU9hmCA3Mz17cyqypzWGbIQiCEDofufAEcgUjbDOEY5wJb6pwtLz45h5aUvGwzRAamJZUgl2DhUM/\nUBBqSO9IMWwTBEEQQmf6lBQnzWoL2wzhGKfuHKIuEb4QMu0tCT50zsywzRAETjlO1kJBEBqbHf05\nDMkcEmpM3TlEvcMFtu3Jhm2G0MCs2TZMS3MibDMEAcepixJPQRCE0OhoSfLM0p1hmyEc49RdDdFF\n587CtCUSIITH9I4Uo1k9bDOEBieiwfa+8ItohcbmpJmTW0QvCHszktWlw5xQc+rOIVIKslI8J4SI\nUiAuuRA2U9uayOR1lFJBG1tBmGxGsuWwTRAanHRznGhE1kChttRdytxgpkRJt8M2Q2hglAKnPrrR\nCw3M0FiZzrYm0aIQKtmiKRoUQkVD0oeF2lN3DlE0GqGzLRm2GUIDo4AdvZKqJIRHIuYuzY4Cw5Tz\nSiFcHEfR3Su1vUI4lHVLHCKh5tSdQ9SSiiG6F8JEKcWMqamwzRAamLQ3emAwU5KaSiF0lFJ87UfL\nwjZDaEBWbBokFovIKaVQc+rOIQIo6lbYJggNjOMoZO0VwmQ0V2nqIZFRIUy6pqRwxCcXQmLlliEU\nSKBcqDl15xDZjiIerTuzhAZi/Y5RcYiEUEklK/1uxCESwmQoU2KsIF03hXB4ZXUvhmFTKJlhmyIc\n49Sd57F7sCBHo0KonHJcGwrRoBAefj+lWFTDFodICBEF0uhICJVIRCMalS5zQm2pO4doRkcKJQ6R\nECJKSVReCJdE3F2aI5rGnuFCyNYIjYpSirbmOM1NMVqb42GbIzQojgJJ2xBqTd05RCC5okJ4uHNf\nxCESwuV9Z80g5qUOt6ZkIyqEg1+74ShFNFKX2wXhGGfG1BS5gi77QqHm1N0KpwAlyhdC4rHfbgOU\npCkJofLm5iHef9YMbKWwbdGiEA6Oo0C5wflMXqckDY+ESaazrQk0TRwioebUn0OkwJajUSEkNu/K\nyAmREDpTW5NEIhq2Lc65EB5KgYNCKUVCWh8LIaAUNMWjEigXak79OUTAyFg5bDOEBqV/tCQtPoXQ\nOaGrhVzRAMCWnsdCSFi2E2xEU8mYBIqESUehcCRrQ5gEYod+yOQyPFaiWXLmhTBRShp7CKEyMFpi\nW28WAJnLKoSFUm6/TcdRoEmgSAgBpbknlXJNFmpM3Z0QtaTiSHNFIUxsRxwiIVxWbxvmxOktADhK\nPCIhHByvfqioWximgy3euTDJOF6AUhwiodbUnUOkaZpMgBFCRXn/F4Qw8bvM2ZaoUQgPTQPDtNE0\nMC1xiITJZdPODCB1vULtqTuHSCklxXNCqNiOwhINCiHj1w5ZUkMkhIQfnTctt9uc1LMJoaCQrA2h\n5tShQyS5okK4OOKUC3XAuu2jADiOrIlCOBimjeUo/mdpj1vcLjIUQsBBToiE2lN/DhGu8N/aOiyb\nAGHS6WpvQjmSryzUD5bj8FffeCFsM4QGxFHuXMBzT53mnpxLDZEQAn5zD0GoJfXnECk3CvWdR1ZR\nLMsQOGFymdrehKMUkhkihMXezrhERoWwcINDbh0RChnMKoSCctzsIUGoJUfUdttxHG699VY2bdpE\nPB7nX/7lX5g9e3bw/fvvv5+f/exndHR0APDVr36Vk08++ZDPu2rLkBcJUJxyXBuZvE6LtOAWDkAt\ndGjZDpbtalAQDkUtNPhfz2wm3RSjozXJrsECtqOIxyLYjkM0UncxLKEOqNU12XfOLdvBUQrLlnVR\n2D+10iD4tWw1MVsQAo7IIXr22WcxTZOHHnqIVatWsXjxYr73ve8F31+7di3f/OY3Oeuss97W8/74\n6Y2cMqsN5ShMy5FolHBQaqHDeDSC4yiJyguHRS00aNo2Z86ZwpqtI4B7QpSMRxkYLTGrMz3h70F4\n51MLHSqlgmuwYTk4kjInHIRa7QuntCSC5h6CUEuOKNy4YsUKLrroIgDOO+881qxZM+77a9eu5fvf\n/z7XXXcd99xzz2E/72hOR6GwHTihK03vcPFIzBMahFro0Pbqh2TtFQ6HWq2FKHcTCu5Xy3ZYuWVo\nwuwWji1qocOdA3m+8dM3AbAsB0dJ+qZwYGq1FkYiGkopbNGeUGOOyCHK5/O0tLQEt6PRKE5V0cUV\nV1zBV7/6VX70ox+xfPlyXnzxxcN/cgUKRSSiYZj2kZgnNAi10GG+ZJIvWdJUQTgsarkWHj/NPQ2y\nbUVE0xjMlCbMbuHYohY6LJatYO6Q6Z0MyQmRcCBqthaqyoBgQaglR5Qy19LSQqFQCG47jkOkKrf9\n05/+dPCHcckll7Bu3Tr+4A/+4KDP2dXVCkA8ESOqWySTceLJeHD/ZDHZr1evNkD92HEgaqHDzvYU\nLc1xSroV2vuvl89d7Dg0tdBgIhknYUM0qgPQlIqjRaCpad/18OWVu7no/OMn6N2Mp14+93qwox5s\nOBi10CHRaPDPZNKt5W1ON8k1OUTqxY79URMN4p4QxeNRTMuRa7LYUVOOyCGaN28eL7zwAh//+MdZ\nuXIlZ555ZvC9XC7HJz7xCX7961+TSqV4/fXXufrqqw/5nIODOQB0w8I0bUolg1y+HNw/GXR1tU7q\n69WrDfVmx4GohQ4N06ZUdr8+8eJmkoko7zm9a0Ley+FQT5+72FGx4UDUQoMvLt/JnBmtmJZ7Qt47\nkKOkW6RikXGfhe04/Oa1buYe33YU727/1MPnXi921IMNvh0HohY63LZrJPj3ngH3/WfGinJNFjv2\ne38tNOinyum6hWnZobz/evrcxY6KDbXgiByij370o7z66qssXLgQgDvuuINf/epXFItFrrnmGm6+\n+WZuuOEGEokEH/jAB7j44osP/8mVP5y1DnuCC3VFLXS4aWeGs0+eilKKnQN5Uk2xSXWIhHcWtdCg\n7Si6e3NM70gBBG3gDXN8ulKhbGFL1y+B2ugwFq1cgdfvcIcEi96EA1ELDSrljWJx3LrekWyZqW1N\ntX4rQoNyRA6Rpmncdttt4+6rbp945ZVXcuWVVx6RQbsG86RTca/N5xE9hdAg1EqHlu2ggK6OFLoh\ndWzCgamVBqu7Khl71XH4lMoWhiX6FGqjw+oGCjM6Uuzoz0tTBeGA1EKDCtcpsr3Or3c99hYff/8c\nLjiji0hEmwizBSGgrg5h2tMJpnek3FlEjsKW6ZhCCLjRKMW2PVmyRSNsc4QGx6rqNldNoWxKxF6o\nGTOnNgf/bksnATdY9ObmwbBMEhoNLyikAFsptvfluPsXayhLoFKoAXXlECncKAO40dD+UemqJEw+\nforStLYmlEREhRBoba4MpLa9TYG9l0NU1C0JGgk14+cvd1fdcjXoKPj3R98KxyCh4fBPiFCgHHjv\n3OmAdDsUakNdOUTZguGeDimFAhKxujJPaADa0vFgFpFlO0HbWUGYTDpam/Bd8WzePaU093J+imVL\n0oqFmqGUos1zzHVvBIY44MJk4saCvD2hIhjFostIFqEG1I3H4c99cRw3Oq8cSMSih/gpQZhYsgXT\n1Z/X3UaGwQnhUBkO7J+aW3s552XDlkipUDN2DRbIFk0AfD9o77RNQagltu1g+cPSUSTi7pZ19VYZ\nUi1MPHXjEPkXe+VNwy6UTbnYC5OOBkE0yrIdyhKJEiYZV4MQpCl5Trm1V72QadlSQyRMCn7A0jBt\nju9Kh2yN0CgYluN2mVOuBn2HvHq+kSBMFHWnKqUUDop4LBLkzgvCpKFVCjhN22ForBy2RUKD4SjY\nOVDp6OV4jlFJN8c9zrYVlqQwCTVkapvbTMF3iEq6tc9JpSDUEg0tKKUwLa+eUoLlQg2oG4fIb6Bg\ne6lKSqn9Lryf/b8vTbZpQoOhlMK2FablkIjWzZ+I0GD48SDlL4Pa+DaztuPWuVm2w/KNA5NrnNAQ\nJONu2rrfXMZxFJm8HqZJQgPhng55neaUhuMthpLKLtSCutntOY5C07yWx47bVKGoW/s8rjWVmHzj\nhIbCChxyRcnYV4OCMBmM5NyNZ3V9ZTW24waNdNPmqSU9k26fcGzT3BRjJOtq0Fde2XRobnIbLfhR\ne0GoFUFQKBjQ6t72g+VDYyWGxkr84uVtIVkoHEvUjUOkvCJi25tIrBTki+Y+j4tGZRiXUDuS8ajb\n2EMpLNumUNpXg4IwmVRqiCon5i+t3I3tOFi2Il8yKe0neCQIR0OxbAXdvPyNqWnaQQbHs8t38fq6\n/hAtFI51/H2h8jrNBbVs3kDqdd0jbN09xvodo1JzLhw1deMQpRIxohEN03JQuFOJY3u13XaUCtou\nCkItSCVj7sLqOeejeYPe4QLgtvq88RvPs2LjoERGhZoT9Sax+w5RvmSSLRqs3zHKS6t7sW23DXKu\n6DpEsiEQJprmZAwgWO8s26FsWGSLJpt6MqzaIt2+hNpRKluuE+T+b58GM6N5A8O0MS13HRSEo6Fu\nHKKte8ZQ3sG8clzhV9cQFcomxbKFYTly4RdqiBuRcpSbOmdaDht7MoDbYenkmW08+fqO/aZzCsJE\nkvI2o35UNBrRWL1liI09o2i4zpDtuPPbciWTMW9ekSBMFC3Nfnqce9t2FBpuOduJM1roaE2GZ5xw\nzLOjL4dlO8GAVscZnz6slKLojR/oHymGaKlwLFA3DpFhOjgOlHULxzsezVelK332316mUDIxLWdc\neohp2fSNFMIwWThG8VPm/JbG8Zgbqc+XTKJRjXQqRt+wLL5CbfHXP38zajmKsmETiWjYjgpawmfy\nOratGMiIJoWJxV8Dfad8eKyM47jBoWzBIKpJCrtQO3TDcscQOONT5vyguGE5GIaNUor+0f2vf0Nj\nJYplOT0SDk3dOEQnH9cGQCIeCyL0/aOl4A/g9BPaGciUKBsWJaOSNrdk/QDPLNsVis3CsYoKBrMC\nbNo5BkDBc4ii0Qh9Eo0SJgl/DbRtt4GCbTuY3kYAYDDjdujsFSddmGCGs+7YAT8in2qKYdoOhZLF\n8FgZw3b41kNvhmmicAzzyPObvf2gGt9UwdOjadroho1lK0r6/sspXlrVy/JNg5NlsvAOpm4cIj/S\n5NcPOY4ilYxSLLunQUpVolPFsskTr3bz2po+8kWTlNcaVBCOFt8Z9zUI0J5200KKuo1jK2x733xl\n3ZDaNmFiiXs1lH61mu2dEOWK7tBqw4uS+qlyviZzRYOXVu0hk9fp6c9Nut3CsUd1yhxA2bCY0prE\nshzWbR9l7faR4LG9wwUKEpEXJoCevpxbO6T8lLlK2+113SOYtoPpuAGior5/zWULuqQTC4dF3ThE\nr63pBbxWnoDlOBimTa7oCtm0HUa9NrSFksnuwQJbdmUolq0gdUQQjoagUYLvFHm3/U5zYwUdND91\naXwN0dd/snxSbRWOfWJeU4XKDBh3I6r8+jbT3Rz4KcR+WsgTr21nbfcIKzcPsXzj/iOjKzcP8crq\nPbV+C8I7nKmt4wez+mtkoWxh2+4p+llzOoJTS4BvPbSSx17a5jrtcm0WJgDHG8USBIdshx/+ZkPQ\nUMFyHDK5/c/HKpYtylLzKxwGdeMQ+cedwRwiBbYDq7cOuw9QiqEx9/g+XzKxlcKwHEqGGbQGFYSj\nwfZOhRzGF276t3XDxnHcvPqxwviIkz/AsFA2pemHcMRU1036F39/E+o4DiXdxnIclKOCdU/3NqI5\n72d39OUo6hZjReOAufObdmXY3ienR8KBiUU1Ct5G0l8L/Zqi3YN5irqJYTnkSiZ7hgr8r2+9SNmw\nOO/UTtrTCV54czd3/GRFaPYLxw6OUuOyNmxH0dmWxLAcdMPBthVvbRsZt37+3JtNJEFz4XCpG4fI\nr83MFIwgZQncTkuOclNF8iUvNaRkUtYtL4XECSKlgnA0/OqVbgplK0gPqV58/a+m1+XQ74DoeMWe\nJcNCKcW3H1rJb1fuDsV+4Z3PI89u2uc+pypdqWzYWJZbXOw7RL4DXiy5GhzN6eiGhW7YlAybJ17r\nJpMrY5g2G3a4qU1jeZ2sd/r+02c2SSRf2AfLVkEqcDAc2NNiMhElVzQxLbfJh2UrprQk6R8psXuo\nQEm32LQzw5yZrWGZLxxD+DW91e3fddOrpbTc2VhjBYONOzM88sIWdg3mWbPNDaYXdUuC5sJhUTcO\n0XmnTXP/4RfQeff3Dhe4/UfLsKsioqbpUNQtDNNGNy1MicgLE8B//nLNuEXX9r6alsPqrUPjnKFM\n3j2e/+qPlvLCm7vdhdl0aG2OByeZgvB2ed1LHYaqKe3ebct2MC0b07ZxPOccKlPbS4ZFoWxRKJve\n2mhTNiyGMmU27szw2to+fvjUBkzLpli2gmjq1j1jbNqVIVc02DUgp0bCvjhVp5QAQxnXwbYdRbFs\nohs2nW1JNu/KEIlo6IZNKhFlLL//NCZBeDsohddlzr1tO+5MStNL1fSDQsOZEkXdYm33SJB1VDIs\nCfgIh0XdOETLNg4A0JSIunVEVYMvp7QksWwVDOOybNchMm2Hsu7+Ufztt397WIuvaYnzJBwYTasq\nILYrnWz+7ZHVmJaD7ThYjqJnII9h2pxxwhR3PpZpBxvRYXGIhCPklOPb97kvcNAdvIiog6MqDpHt\nbVKLZYuRbJmSbmNY7sm5G0W1GRorMzhaYjBTZtnGQUqGRbHk1R7pFrsGCry2to/nVsjpprAvezdV\nSDfH3bR22+38lS+5cwIt2z3FHCsYjBUMojFpyy0cPY7nDPmOuWHaWJYTBIb8vWGh7A6pHvQcI8vb\nI+qGe+3OFgyWru/nldW9B3s5oUGpG4do/Y5RgMoi6y3Ag6Nuq23bqUQByoZNqWxhWm50wDQd5sxs\nZZVXb1TtTPk8v9xtzf2v/yUtQoWDoMZPZa/+unl3BttxCzoLZZOVm4fQDZtCycQwHfJlk4KXr1zS\nLd5Y34/tOLz6liy+wuHRkopX3RpfywYEjo5tq0CXvuNeMqygBbdhuqkkhmlTNh0KJZOs14Wub6RA\n2bDdVBLDplCyyBUNRrO6OPPCOPzhwEEasX9SZDtkCrp7aml7dW0odMtd+zTN1WC5LJF54eippLG7\nXw3TwbSd4KTIx2+g4KcN94+WKBs2hmWzasswj7/STXdfjre2DQFugGl/+0WhMakbh6jSYtZNl/M3\nAYWyRTwWcaMAXkQ0XzLdyKeXFuKmMdlBGtPn/t8rlHSL//1/X2bPYIGdAzmeXrqTsmGRyevyByAc\nEL/FJ1TXDkHXlCZGsjqO55g7DmzrzVI2bfJlE9txGB4rUyxblMoW3b1Znlu+ixUbB3n8lW6gspkQ\nhAPR7DlEsagW6LBaN1ZVzryvT38mh27Y9I+6DpFpO5QNtwOT7jk/frfEQsnNqS/pFv2jRUq6Sb5k\nkisabidF4M6ful0TH35hi+i2gfFPH/30Sn9DmiuaxKLuddm2lbsRNRyKZbe+17LcukopZhcmgkoN\nmytA066kr1fXB5UNG91ygj1iT18O3XQDQ7sHC5QMi1zBYCDjBn5+8j8bWdM9su8LCg1J3ThEF54x\nHajKm/f+UdQtHOXlz/uRUN3CtOygrad/8c97EdD2lgTLNgxQ0i2Wbx5kbfco2YLBtj1j5EtuFF8Q\nDkSQohRMw3aHv8WjEayqjWh3b5aS7tZiGKbDnuEi+ZJJ2bDZ3pejtTnOrsECybj7Z/aVe14PCj0F\nYX/MmNoMQETTghMgpyrL1/Dr2GynMpPDrqTM+Sc8lucIGaYbHS3pdlV7bgvdcCjpFtt6s9iOm2pS\nLFvkim765+otQ2QLBis3D7F7MM/Tb/Twxvr+yfoYhJB59QAt2YPTc6/Bh2E5QR2HX5vmF7qbpo1p\n2Tzw9EbpvCkcFUHHV09Gfpqc5bjdhn1KhkVJtyh7zUA27coAoJsOuZJBwdv/jWbdGriRrM62PdnJ\nfTNC3VI3DtGvX98BVAqIq3NFS7rl1RC5ws8W3U50pu3+Mdi2Qjfd/FBHKUpli1VbhrAdxfBYiVzR\nQDdtlm8comxUTpIEYX/snR7iF2260VCnkkffFEc33ei7AgZHi24reN0iWzDIl0zyZTPoxtSSigep\noXtT8vKdhcbG155hOfvoEPDmbrgpxb5c/Px5BQxny8HP66a7YTVMh7JhUfJmZxXKrh4dBdt2u5uB\nYtmiqFsUyybrto8wMlZm485RCmWTzTvHWNs9wutr+wB4edUeVm6Wye/HMot/tBSo6NEbiRWsfdt7\nc0F2hqsvG92y6R8pUfJOJvNlC8N0WLt9hKUbBsJ4G8Ixwt6dX02vfsjyHHEf3XCCFDmAAe/EXDdt\n8iWTkm5T1N304T1DBTJ5fZ8RGj6PvLCFobFSDd+VUG/UjUPk40c7naqNgT9Uy/9ewSsG9qOlpu12\nXsoWDQZGS4wVDUY9pydfMgPB7xkqALB7sMC2PWPjXrd7T5Y1W4dq++aEdwTB8Leqxde03S6HtlNZ\nlP2ToYJ3Mul3lyvpFpm8QVm3yOYNskWTLbvGyOQNRnJlRnN6Zehr2WTTzlF+9uJWXlolgzIbnv2k\np1Wn+JpVKSJ21dR2H7+xjN+V0+9MVzZsyl7XpaJuoXsbBr/mqKS7HekMy2HllmEUsLEnQ75oksnr\nDGfL7BosYDsOr7zVy9INgxTLFv/zRs/EfwZC/eBpL+p5RH7QJlc0sO1KY4+Slybnb0R10+2EaFg2\nHS0J1mzbf1rShp5RqeMQDkmlsYx3Tbbd5kZmlQbBHVxtWva4zpvgBpIKJbfhgr8ObtyZYaxgkDuA\nQ7Rl9xhLNwxw96Or6O51A0cPPL1xXE2ncGxxRA6R4zj80z/9EwsXLmTRokX09Iy/KD7//PNcffXV\nLFy4kEceeeSQz7fon39T9dxetLMqL77kHX/67bV9kZvelGLDrLRC3tGXxbZV0HIxXzIZy7uCL3hD\nCt9Y38/3frHGjTDYDoOZEkvW9/Pyyn03pP4cBqH+mGgdBnjrnb+o5oqG12FO4TiVE6J8ycCynUCf\nOc8xKhs22YJBoWyR9WZnrdo6zFhRJ1swuf+pDbywwm3y8fgr3by8upeB0SI9/Xn+7aEVPOWdlv7w\nyfUUSvtfrIX6YKI1uL9LbfVe0aoqIq7MyapsCIpVE9ndzUElgl/21s1S2d28QmVNLBlWoGM/cLRr\nsOCdOrlR1OGxMis3D9HTn6dvpMCrb/Xyu7V99A0XufsXawB4ZulOaXEbArVaC/36tMqQYPdruslt\ntuA75/7vPOttLnXTPTFym81Y9I0U93nurz+wnG/+9E3ufHgldz68atz3TMvh6w8sp2xYvPZWL4+8\nsOWwbRbCo1Y63LvLYaXDnB00lQEoGbbXUMZrwOWth7rpeOnslZlE3b1Zt3ayZLBswwB9w+669/ir\n3Tz6262M5nSGxsq8uXGAp9/ooVA2eWN9P5t3Zdi0M3NkH5BQ1xyRQ/Tss89imiYPPfQQ//AP/8Di\nxYuD75mmyeLFi/nhD3/IAw88wH//938zPHzwuonqFLZ9utmoynA4PzWkctsJiut0y6FYtoJ8UD9f\nvlCygtOiolc71DdSZCSrs2R9P7/+3XZ+8Mu1DGZK7BnM0z9a4LU1vazcMsSa7hFuu38p/SPFAy7I\nG3tG9xvdkohX7ZloHfr4U7D2bq7g1m5UaoiKuj1u6Ju/uVTA0FiJQtkKnPH1O0axLOWm0hUNevrz\nrNs+zJptI4zlDQbHygxmSnTvzvLqmj4GRoss2zDAC2/u4Rs/XeHVeFSmcJe9wZv7I1s0sB1n3ON9\n+4WJZaI1uD9nonot8dc8qNZl5ftlY3z6iF/PUSybgU7zVTWUvgOl6za6F0TyB7Zmcu662TdSpFh2\n00KfW74L3XTbeG/vzzKQKfHcil2s2jLEsg39PPbSNl54czd3Prwy2GD4ZAvGuBo623H49e+2o5s2\n//nrdYHDJrx9arYWqr2/uv/wsy786Hxwamn7qe4OluWeUuYKBsWyGZxe/uq17dz9izUMZ8ukElHi\n0Qj9I8Vgvdrem+WFN3exZfcYdz28ivU9o6zaOhw4/qu3DvH0Gz2BLaZlB2uvbths7Bl1T6dMm3Xb\nKydTSqlx6VXCxFO7a7L31f+de2ugaTmB0w6uA6R7gXIgCIz7KXO66QT37fYCP5m8wYpNg7yxfoC1\n3SO8sHwX3Xuy5IomfcNFBjMltuwa43dr+iiULVZsGuT7v1jDrsE8ewYra9xgprTPvm/3oDue46nX\nd2BaDrliJcDpOIpHpGlNXRE7kh9asWIFF110EQDnnXcea9asCb63detWZs+eTWurO6H6ggsuYOnS\npVx++eWH9dxBDVFV8Zy2V/6yv2kwbTeHFK9Vd75k8pZ3NO+fIo0VjCCS6l/8/SjWS6v2gHIjov4F\n/65H17B7qEBHa5JTZrXRN1Lk3l+to3+4wPSOZlZvHeLkWW1s2plh+tQUyzcMctnvnUjfcJF5Z3Qx\nmtMZGC2xvS/L3DkdbN2d5dqPnMZgpszZJ09lyfoBlOMwmjO44MxpTO9oRtMqsxrcCczvwLmnAAAg\nAElEQVRuiksiFqGoW5QNi+M60/SNFJnWnkI3bVLJKLatiMUiKKXQDa+wWjdpTyco6TZt6QTFsklT\nMoYGaJqGUip4PeUNwFVKEY3UXfbkIamVDvd2yoOBwJYzLj2p7NUO+YtgqSo6X/CaK8Si7n2j3uYy\nk9eJRDTQ4PWf9Qf1SdmCgVKKbNEdcvgfv1pHybBZtmGAnoE8P3h8Lf0jRW751DzW7xjlFy93c9Ks\nVmZ2NLNxZ4YPnTuLDTtGmTYlxUsr9/CuOR3sGS7wyYtP5Y0N/bx37nR++uxmPnTOLMYKOqcc1870\nKU109+Y499ROprWnsB2HeCxKJl8mq9u8sWYPJ81o5bU1ffzhBSewvS/HvDO6GMmWiUY0Xl/Xz8mz\n2ujpz/G+s2YQi2qkknFiUQ2lIBaLMJrViccj9A4VOWlmqzu00dPvuu2jnDSrlZExneOmNdM/WmJG\nR4pC2aIlFUepytBHcDtR+nOiTMshHo/gOIpY1OtQWaXt/d2uxlGKyAG+93aYaA2OZPdte12doVGt\nv0oXxMp91R2XDMvGst3PwHFsdNMfW1DlEHnOUanqPr+jmP/VT6sDgi52uaLJtt1ZSrrN2u4RDMvh\nF690o5s2S9b1s70vx1MtPTQnY3T3ZTn1uHZ6BvL09OdYdNmZ/M/SnczqbObVt3rZunuMlVuGScSj\nDIyWOPfUTmxHce6pnRCLBX9fCsb9zvIlg6de7+H806fR2hwnXzI57fgplc/CsInHI4f8Pft/d63N\n8XGPVaqSaeB/brGoqzlXixq247dAV5QNi/aWBBoaJcMilYjhKFefjlI4jqKoW7Q1J8a9xmhOZ0pr\nMliH3Tl87u/V7756KGp5TfbthIoW/cZEQdaG9zn5XeX8tdDyUppM2+Dzd70KwHvnTmeTl64EsGe4\nwEhW567H3qJYthjIlGhPu5/Rhh0jNMUj7Bkq8POXutE0WLZhgOFsmaGxMtt2j5EtmjhKccPHzuS5\n5btY0z3CezxNLNswwCc+eDIfnncC9z+1nh19ORb+4elMaUnyxKvddLanuOqSU7BtxcMvbCaVjHPF\n78/h2eW7iEU13veuGXQP5Hl15W7mndHFCdNbWLK2n5OPa+M0b2aYZTtEI9o+a41lOwxny0xtbSIS\ncdctf606Vqm1Dv1rsn/CbVbVWgLe7CEFjM8mAnfNsh0V1MP5wcqxvM7OgTwjOZ0X3txNtmjSO1JE\nN232DBWwbMVITudlb3bRqi3DZAoG9/xyLdOmpPjQOTNZun6ANd0jfOicWZi2m63U2dbEyi1DzOpM\ns7FnlK17xhgYLXHtR07nueW76GxL8dzynQxnyxTKJh+54ERO6EqzoSfD771rRqCZ0Zx7Qr+1L8+a\nLYPMmdnC62v7+cQHT2bp+n732t+TobO9iaXrBzi+K01Ztzlz9hRmTk0xmtNJJmJENGhLJxjJ6Rim\nTSanM3tGK81NMYq6TbopxpubhzjjxHb2DBU4vquF/uEiU9uTlHWbaVNSRDT389INm5FcmWntqWB/\nblpOsF75fw/FsklTIoZlu9+r3lvt/bdg2U7ofx9H5BDl83laWlqC29FoFMdxiEQi5PP5QPAA6XSa\nXO7tTz+vTMauqN1Po7OqNgIKsJxK3ZF/2uRHCNwZRpWolXufu2j39OdIxmNBowWlFP5vdzSns0W5\ndUZ9I0WKus3PX95GtmDQM5CnpFvsGswzVjB4bvkuRrI6W/dkiUQ0SmWLfNlkz3CRbMGg/xE3XeC4\nrhZ29GaJRSOUDbcDXiIepWtKyts8a2QLRtBKMhGPontpL1PbmxjKlOloTVLS3Q1j2bBpSsaIaBqF\nkkE0GkE3bNKpGPmSRWd7E6M5nfZ0AsO0STXFKJUt0qk4jtclKBbVMC2HjrYmckWD9pYkhmkTj7nP\n1ZSMuQ6ogmQiSq5o0JJKUNIt0qkYGu4Gt7kphu1tTh1HgQam6ZCIR1w7E1EcpdDQiEbdP5ZoxG0t\n7DgOEU1zF6uIRkTT0DSY2Znm6ksrWppsHfp/vH4Efm9NWrYKTpOq9QWg+5HTqhxmX3sKcJxSoNFs\n0cCwHMYKRvAce4Zdzfgb0K173I52ix98k0hEY2isjFKwaecY2YLBcLbspvR1j5IrGqzdPkK+aPKT\nZzcxOFpiTbd7EvXcCjfCv2b7KBowktV5ff0AzU0x7/cepaRbGIZNvmQQi0UZypTYuGuMbEHn2eW7\nKOkWqWSM3YN5pk1JkSuaLN04SDIRBQWJeBTTdohFNMYKBsl4lGLZpDWdIOE9fzwWYXisRFs6SaFk\n0tIcp1g2aUsnKRsWLakESinvAuZqI5mIYnsLa7FskfJsbksnUMrdhCXj7vOnmmIUyxbpprj7fM3u\n81mWQySikfM2wIbp0Jp2vyZiEQzLDhZl03JIxKPMO3M6l//+SfvVyERr0C8CPhDKUfukL407QarK\npw8GC1s2VnXQpeoxfmqJ5VQ2Fr5W9UCz+zpLQHDyPpJznbjhbOVECdwc/WzRoKzbDGbKbqF9yeSh\n5zczktXpHy3iKNjiNXZ4a+swI1m3xi5XNHh9XT+W5TC9oxnTdlNjOtubiEYjwQV9w45R1vdkguL+\n47rSWLZDSyrOwGiJZDzK1LYm73cZoaRbgU7aWpKAIlcwGRwt0tHWhG07tKaTwWcwmi0zpS2J4ygK\nJZNEPIph2rSmE0xpSTKUKbkOu6ZR9tZlLeJmJrQ0xynrFs1NcXTDJhrVyJdMprQk0XCvX9GoxmCm\nREdrE7ph0Zp219Z4NIpuWrSlE4B7Xbjlhgvp6mjery5qvRbuXTbhByYq12RPR76e7PEaq3bal24Y\ncINCHr5jtHFnBs17LaXc+wZGiyTjUcANYLopoO4a+rs1feNSRH/67ObgFGrdjlHamhMUdZsnXtvO\ni6v2kM3rFHWb/3p+C7GIxs6BPMl4lC17skQisHVXhmQ8ytrtI+wezIOmsXTDoNuefqTIhp0ZmpMx\ndvTl6GxvYtY0d+NpmDbpVJx4PEI2bxCNaHROSZHNuxqf1p7yPhPFzM7mYH0p6RaRiEYsogXBtmTC\nXb90w6alOU4iFsWwbJLxKPGYO7TeD+a4Trb79+1fr21HBdd3f3MaXI8td8NZ0l3HPhGPgCL4XWia\n5u6nbAcN937lXZN95sxs5U8uCf+aXHHQ1TiHyP+79de+cWudaaMUaN778Z0l3XQd15GcHjjy/klO\ndUfiAS8w5O8xh8bKlA2bB5/ZHAQ8X13TF6yR7S1JsnmdQtlCNx029mQolC1++NQGhjJlWpvjOMrV\nqmk5DGY2E4tGGMvrLN04iO0oTNMmVzSJRDVs22Esb5BKxhjJlunuzTGYKfHGhkGyRZ32tLsedbQ1\n4SjFq2v7XGen7K53/hpY1i2SiRhlwyIRi9LcFKNQNknGYwxmirQ2u4H0dFMcy3bcPaBlk25KEI1o\nwfU7XzRpTcdxHIJrZyIeRSnXIYp6+9lU0n2tdCqBadrEYhEsy6EpEUOhgn1jvmjS5l2LW5rj3mGI\nhuk9r6Zp3p40ysXnHc/F8054W9o5HI7IIWppaaFQqBwV+oIHaG1tHfe9QqFAe/u+09cPRTSiBRcM\n90NxNzJ+1MwwHeJRDVMpErFosLmfObWZ7X05knH3vhZvccgWTZoSUYq6RXNTjFzRZO7sDhyvLmRK\naxJHQToZZc9wibbmOKed0M7Lq/Zw5olT2N6X46ZrzuPl1b2cOXsK67aPcvy0NM8s28mCS0+nd7jA\ne+dOZzBTYihTYsvuLOedPo2NPaN88pJTXWElYgyPldyLecHgtOPbicei4953V1crg4Nv34GcaOrF\njoNRax1GNPfi7M/BikY0bFsRjWhYjiIe09C0iLtwWQ5NyWjQ8COV8DfmcUxvUTAsg5ZUnEhEY0ZH\nik27xnAcxbS2JkbzOh2tSXJFk3zR5N0ndbB0wyAnz2pl084MH3j3THoGcvzDwvewZ6jAQ89v5qQZ\nrZw0q5W3to3wxx84iaUb3OjQL1/p5sK509m2J8v1Hz2DJev7+eDZM7nniXV8/H2zGRrTOfX4Njpa\nk+RLJtPam8adEDpK0dnZwrK39jCrs5kl6/v5wNmzMC2HdFMsWKTW7xhlVmeaPUMFzjm1MziF3Bvf\nsdk7+mN6zseBTnGgPnTY1XXgDcBEa7CjNbnPfRqVk3N/c+JHOh3lnprY3q4g4a174J7Q2bbr1MWi\nkeBCXf2YVCJKoexeGJVyu3U2JWLkSyappPu1JRUn40VTp7QkGMyU0YBZU5vZ0Z/n+M403X05TpiW\nZuueLKcd386GnaNc4EXUN/ZkOOPEKWzYMcrmXRluXnA+v3ilmzkzW3n85W4+dM4snn6jhz94z3Fk\n8gbnntJJMh5l9sxWTjhuygF//45SLNswwFkndZBuiuPU6KS7HjQIHNAZgslYCzUvoIV3Ku7dH9Fw\n7Mo1ORGPoJvOOI0l41GiEY1cyeS80zppTcXp7s3RN1LEdhRd7U30jfz/7Z15lFTlnfe/z/Pctbbe\nd7qbvWl2WhBFwIAiKOgYFdlsTELMvJPR40TGiPiaaOIEZ+Jy3jcmRs3LOBJOMmbU8SRxOSZGnahD\nNIg6CkgIm4qsDd1d3V3rff947r1VvYAsXX2vXb/POR6rq4uqX1V/67nPb3l+v04sPH8o2jrieGvr\nQVQWB/DX/a2oLQ/DUDl2ftqKpXNHor4yjJ/95kO0tMXw5dnD8f5fj+J4ewwpy8LfXj4OL721D1t2\nHsb0sRXQVYE3/+czfOOKcRhWFcFzb+7B9n3H8LWFYxDQFfzmjd2oKQvh3MYKWJaF/3pvPwxN4NzG\nCuz85Dh0TaCmNAjF0PDSm7swrbEcIUPF0dYYCkLagEez/aLDkzFQ12RnLyg4c7OpgBwkHO1KykBv\nyuq+1ukKEqk0BGPojKcQMlQcj8YRMBRUFJkojhg4cKQDHx+Oojhi4GBLJwpDmtssaWhlGNv3HkNl\ncQB7D7ZjWJW8hq6YNxq/e3sf3t52EJeePxRt0TiOtcdQUWzi1Xc+xajaQrz5wWeYPakaHx9qx1cv\na8SLf9qL6pIgNr70EeZPq8Wx9hj+ZuZwBHQFHXZgJZtoVwLBkIH3PzqIIaVB/Nf7+3HZefXY+clx\njBpSiKg9C/Gdjw6jqjSIWDyF8cOLwW0nt+e1OZGUHUiDRvfX6Ywl3eC1HP1gyYoPZLLzftDhya7J\nZ8MZOURNTU34wx/+gEsvvRRbtmxBQ0OD+7vhw4djz549OH78OEzTxFtvvYVVq1ad8nM7C67zt1ME\nd7MYQsgvgaYIxBNpKHYERBEMquAImArGDy/G7s/aYGoy8xMOaGAAWjsSdmowiYKgzLJcOr0Onx6O\nIpW25ERuzvC/Lh9rd2eS5z0OtnTihsvHYvP2Q6gpC2HpRaMAAFNGlQEALphQCVURsrwDQHHEQENd\nES6YWA0AmDyy1H0fAFBiR4uqSs/kkyeyyZUOnegns2840RVV4YAlHXOkLQQMBYJzdNpZvICuuA5R\n2M5IBA0FrdE4yotMHI/GEQlqMDSB6tIgVi+djHU/34xwQAMYQ2nEQDigI5lK4foFY7B933Gc21iB\nypIAllw00tVQfWUYty1vcu2dPrYSALBoxlAAGW06XDq9HgDwj0un9HqvPRdEQC58iuAYYZeEzJki\nIzFOpBaArXkp4rJC83M+TwZF9HZ6egYDvoj0twZrK3ov9E6pKwA3QJSKp2SG1XbQnQ2BnrUB0BSO\nBJNro6ELJO15bTJil9kkRLvkRdCygFgi7pafOf8vLwq4DlFNaQiHjnWh0C4pbmmPYcKIEhw81onm\nBQ144Jfv4rzxlaguDWDh+fUIGCrOHyf1ed64CnTFZDb564vGAgDqK8IYOaQAJQU65jQNOa0yRs4Y\nzm2scH8W/VAC+UUll9dkwL4eWxktlkR0HGmNQVU4kqkUTE1BPBGHrgnEEmn3+qsqMhMRNFX8n5tl\nKdVbWw8gHNTQ9r4cn1FZHIQiOK6cOQycMzTPb8DbWw/iZ7/9EOeOq8Sho1GkLQvnj68EYwz/sHgS\nol0JVJeGcOHkmm52Xje/ASus0e7mb/60Opm5BnDZ+fW47Px697Ffnj0i6/0xzJ5U7f7srH2AvKbP\nzYpGlxQYp/XZ5RM5uybD3hdyBtibdCc4nso612vqirtXTKQyax0DEA6o6OiSWbnOeApFYR3Ho3EU\nhnQMKQuhqiSI5RePwg9/8Q4qioNo74ijujSI9s4EisI65jbVYPveY2hqKEM8mcaNV02A4AyaKnD5\nBcNw+QXDetk9c0I1GJPX5Ia6TDnv4i+NlPZqsgIhm57OECCv02VFAUwYLveZV9iv1VBXBEDuNwBg\nTh9Zk75WRVURfV5/TV26BM5aqirshM8xGDkjh2jevHl4/fXXsXTpUgDAunXr8Jvf/AYdHR249tpr\nsWbNGqxatQrpdBrXXHMNysvLT/p8zZeOwYbntwHILLjcFb6d2u1MQhUyCmVoAu2dCSicgSnCrU2M\nBDQMq4oAAExDQUt7DCFTgSoE9h5sR8BQgOPAsKowOmNJjKgpwMghhZg1qRrPvPZXKKqMfhua/FhC\npopbl8lN5IwJVX3aPhg2dV9U+luHDgwMFjIbTaflrMI50iJz9sTUVXuhthDtlOVZh9AFzoDSAgOp\ntIWCkIb9Rzowbmgx9h1sR2FIg64KNNYXQ3COSSNK8dnRKCqKTBSFdVSVh1EUUBAwVCw6vx4zJ1ZB\nETUnsZbwkv7WYF8XHmczCsjACueydIBzDqRkls0pfTM0geN2ENbQBJgdtQ/YG4WuuKwVd0o8nDVR\nRgUBRGUWaP+RDpREDOw/0oHKYhP7j0TRGUti0Yx6/OWT4ygrNDB8SAH2HWrHvGm1AIC68jBuvmYi\n6qvCmGE7QdlwxuTrZTG6Vm4SLjqn9hQ+beJE5GotdNZAx9fkHEinYF8jY3YJbEo6HVG5RgKApnJo\nCoeuCUTsUlmHaY0VmNZYgYCm4KnX/gpV4RhdW+hmPzljmNZYju37WrDyska88c4+fHo47Do5BSEd\nBaHemVSH7Ei44wwRA0OudOh4RJwxpGBBVaTjrSoCDJmucoauIJZIgTF5rs2w//6GJmQJWNqCYuus\nrjyEvQfaEAmqmNNUg9ICAyFTw5Uzh6MjlsSBo1FUFgdwLBrH8MowJo8sRVFYxzmjy3DJtFp3n3gy\nHE1nO0PZ9HSGCG85I4eIMYa77767233DhmW84zlz5mDOnDmn/HzXXtzgOkSKYIgnM5tOXeWyZhIx\nN8rseLGaoiCZls0HLMtCJKhhaGUEmsph2l+EkKm5XwrH854yuhTXLxjjLpyMMcxtGoJwgdl9LDzh\na/pbh5nnBWABQnAgmUYkoKErnoQQDMLi7qY1bCqIJdLgTMURxBAOSH2ZuoJIUENbRwIRU4PgwIQR\nJXjjg88QCepYtbDRfa2FM+oRT6Twwqa9qC0PYcHMEW46+uKptEn0O/2uwT6yHJwBztF+hTM3M+5U\nh4ms7JvM+Mlad0NTkEonoanC3SgAUp+y5jvtrommrrhR1rqKMLbuOYYh5SFs3dOCorCOwpCGkKli\nWFUEw6rCKI4YmN5YgcKghqCh4spZw+V7r46c+nsl+o1crYVOaZKjMGYvjo5DralShLoqwJl0Vo62\nxaCpMlCpCo6goaI40tuBWThjKC45t67PxhGMMTTPl9fo0bVFGF1bdNq2EwNPzq7JsJuq2A6GKuTZ\nK2fv52CoAh2C2+eEEpm9oibkmdFkyi2rHV4dwbs7jyBiyn2jw7ljZdb5rW0HUVEcQF1VAcbVyeMN\nl88YiurS4EnLvIkvLr5reZKJEsmfNVVk0ni2kJ2LuKowKFzWxysKRzigojCkIWyqqCiW9dZhU94H\nAMOqImAAKosC3Q4KAkBhWEdlSTDXb4/4AuFmhhRZQubUwjv3B00VuiYQNKU+ndIxQ1NQENQQMKRj\nFAnqqK8IoyikobSg+8aA2xnJK2cNxzkULSLsi3v26pR98VUV7kbbnfVQZK1lhWG51ikKsw9iy8cb\nWetowFCg2eWPVcVyzTM1xf5PYMroUgjOMG5oMUKmipKIgdICE3UVMkp/6Xn1mDOlBorgGDesJDef\nA+ELHGUl7EPqTnS9vjLsOjwMMgIvBIeqcHAG99yapnJs3dOCmSessPDdFoTwIc4aqLjXZA4hZCl2\ntoZMXUBXBTT7voC95umKQNDUYOoKDF0676OGFKIgqCEc7F2iBgDTG8tx3tgK/M2FI9yM5Jem1JAz\nNIjxzWr05VkyiuBIzckQaQp3L+xOZDQcUCG4/FJoqlyEdUWm5hljCJoqpo0pg65ylBQYKAjpCOgK\nzmkoQ8BQTppuJwhnvXM2mqpiO92CQ3DuRuRbownoikDAUMEZUFEcgKkJBAyBorCOoL3xdBoppNK9\nz/cQRDbM1Rx39detBMi+2Gc75tn/d84oqrYDrymydMnQlUwpsKG6zzGiRkZGA6aKgKEgYCgYWV2I\nskITw6sjCAVUNNQXYcaEKsybKuvTx9QVoa6Ps07E4OGnay6SN3rs/ZxAYmmBAU2xr72agKkp0FWB\niiIThiagKvI6rKkCd648xz3rQBBngrMf5FnrI+cyUKllNbfQNQFDF66TVFMmAz7yHJsCU1cR0OUe\nsKzIRGFYR+EJ9oOzJ9e4QSQiP/CNQ/Ty5k8AoFsZGwC52bRbU6q28GXJh3APbCqCw9SFGw2wLGDc\nsBLUlIUwa1I1Jo0oQcBQUFMaQshUSeTESelr8VXdlszMjcyPH1YMQxfynJrCUVEUQNBUYWgKhlaF\nse9gO85pKHPnuKxtPoc2ksRJ2bG3BYAcLeA43tkZIFXhbqMZN4OZtS6W2ge+VSE3qprK3Sy7sz6a\nhty8BgwFw6oiUBSGoKEgaKgIBTRwzrDg/KEwdQWXTa9DWYGJc0aXYXj16XcLJb6Y1JTJ1skM3Ss2\nuq2JdkZIcGZnIjlCpgpVEdCd67PCMYx0Q5wlTnmwc21WFQGFy7VQzWr2Y2gKDFXuBRmAUUOk9nRV\noCAgy36DhorisA5FcNSVhzB+OGW5CYlvPAPn4s+YXHydhTccUNHWkYCicPcMUchUodkTri0hg1hd\n8TSqS2U04O6vnQsA+N8rp7qP/9a1k6Aq3G26QBB9IdtTyttK1ob08PEuTBtTjj0H2sCZ3IQOqw7j\naFsXQqYKRXCUFRoIGApMXcGI6gJ85yvTYOoKHrjxAu/eEPGFImB3/UunLTBnTcwKWyn2RpRzBu7o\n03aIDE1G6AG5YXUy67ommyqk7fORIbvUM5WWc30CmoKwqSKVttzy4qvnjsKhQ204f3zfpU5EfuCs\nhQFDdhx0ApVBU4EQDKqQGjN0RWaKbMdbERyGKqCqvom5El9gWM8gpX1MQhGsW/tzQxPQNCHLhHUF\nteVhmJqApgqMqClAW2cCQmS6dl514YjeL0bkLb5ZrWZNzLS85Jy5C3FpoelGRJ2SOd2OADgRKGeC\n/bihxSd8/ir7fNA3rhiXuzdBfPFhWfXKItPWHQAqSwIQTGaIQqaCxvpiufDa5SKmLqPspiaHiDmZ\nyFPpRkMQALDvQPZ8h0zXLQdVkRf37Iy5kykydYHSQhMM8gyHpkqnyNAUhEwVBcHMWUpdkxkiRXD3\nd+VF5ue2UCfyC6c9u9tljjlBIo5wQIOiyEylJjIl7o4TZBqK29yIIM4GzmSuMnO2PBMY0lTu3h80\npENeFNbdIxOGLkvXR9cWYvGXRmDCsBIK9BB94pudmhPZ7IwlIQR3F15myUPAnGU2AIrgrkOkCI5k\nKo07r5/mme3E4EHOH5K3nY2mrgr85JbZ+P2fP3brlmsrQlAEx6dHohhTXwhV4QgaUpM0p4I4U462\ndvW6Lztj6QaAeOYwseOwB+xSkICtQydLJDhDZYmJZNJAXXkI44YV45V3PnFbJJu6LJ2rqwwjmaIu\nm0RveI+sebQziXgiBSF0qIpAKKgiZMjMY2FQRySoIZZI4Xg07qHVxGCBMec/2/FWhSwbFtIxEoIj\nbQ8a1dU4KosD7r7R0AR020mXXQv7boFNEL7JEG3dI2vnXWfIXoAjQQ1/e8U4eVjOjjbpKkfAroPX\n7W42BHG2/PCmWdAU3usMkSI4DE2R5UoKh6Iw9yDmPy6dgqbR5W5XpXgihfoKKsskzozLZmRa1DqO\nkHOOQ3Dunt3gLNshsh0bO1MZDqgyM2Rnhxrri9BQW4SmhjLcft054IwhZKgIBWQ8bMaEKgytirg6\nJ4ie9CxZKonoKC00IRiDrspOhjs/PY6RQwrRGben3acthEzSE3H2cMZkmXBWtzldE1C5rBJyus9V\nlwZRUx7C5JElCOiZkQLZQ8UJ4kT4xpNwovEFQU2eIcqqVQZkzagzjTcc0GBo9hBVXbgtZAnibBhV\nWwhDF64z7jpGTsbI3oQqdlQqG1OXevz28iZMa6T22cSZMW96fa/7nM2oEAymJh1vzph7kXcco6Cp\ngjGG4rABQ5M19AFdwXnjKmHqMlrqDKqMhDUUBKVTP2dKTa8xBASh2qMsgMxa6DjpyZQlZw2pHMzW\nYtqSlR7VpUEYmoJpjeUUrCT6Byb3iG71hpAOkqrIpgpCcFQUmxhZU4CLmoagMGzgonNkV8wAOUTE\nKeKb8E25XTLHmGw9Kw+uM4weItObnDOUFspSpKCpgDHAsiyYmgKLqjyIfsCJQFmQPlF2223AGXop\n73eccweap0H0B9k6clwUZ08pOIOhK0gm0+A84xA5AaGgIZfzscOKsfdAG0oixglL4M4ZVYZoVyI3\nb4IYFCSSafcMkOMwOx02aytCONDSAQBumfD6NXMBAFt2HMb0sRWYMqqMxgwQ/YI8V8666bArloJW\nKLtpCsHQWF/ULTg+3R6wGjAUt7qIIE6Gbxyi8cNL8OQfdoLZh+fkUDeBoD2ElSFTphQyNUweVYq6\n8hD+Z9dRpFLWSZ6ZIE4NlqlRAueZTUDA3miGgyoYGBTOex0WXr1k8oDaSgx+YoFpZoQAABtsSURB\nVEnpzLitj7ls1NGeSsj10Rk+aOvTGVg9b+oQ7P6sDXUVYaRO4BANpW6bxCnQ2iGd5p4D0w1VuAGk\nHR8fx3WXZM5N3n/jBT3HFxHEWSHcpgqZzq83L56I3765B5qQJXMFPYKUDkFThUGjVohTwDdhbSda\n6dSKMsbQ0ZV0PXvOGcoLTVk2ogucN7YS1aUhlBYYaO2gg5tE/8Dsck3GMvXKB+05QkFDlY6SYCgM\n03BfIrek0zLQ47TdFozBUAVCAdWe0C7XxuKw3IwW2BPXVUVg1JBCe9ZQ31PYCeJ0cGNFzqF2TaA1\nGoeqcKxa2Ija8sx8NWf9JIizZeLIUnsUBuvWVEEIjtIC022/rSr8hPMlC4Maygqp0RHx+fjGbd5/\nWKbfO2NJ6RQxOWXY+QL85ZPjKCkwYKqZAYMA0DS6nNLyRL/iOEXObKxpDfJMUNBUYQFIpdKoLAl4\naCGRT7hNFYQcRJ1MW/Z8IekQlUSkc15dGvLMRmJwUl5k4mBLpxsciiVSUBWOgqCG4ogBVeG4YAK1\nMCZyw5J5o/H+zsPgtjPkDGh1mihoipx3JTh3M+U9ufS8+m6jCwjiRPgmQ1QY0qFwhlBAdc8RZTs+\n69fMRdBQoSqsVyckikYR/YlTqyzss2zH7QxkQFfw8cF2fHwoiopCcoiI3BK2S+CyNwGhgIZYPAnB\nudtKtjCkQ1M5SqndO5EjnA1lScRwB6ergiGVpnJ1Ine02SWbjHev2nCClaoij1ZwxlBTFuzzORR7\nXhFBfB6+yRCVFRpIWRbSKQvM7iii9BCxoQmodu0yQeQG5g6BE1yWJU0ZWQpA6m/8sGJ8bWGjW65E\nELmirdPeDNibgJRlYcrIUoysjuCjfcfBOYfgDJGghpChIhzsu4aeIM6UI8flXKzus9nkGnmsPY60\nRQ4RkTsahxZDFdwum8s0OhJO10PO5IBphaEkQkOlibPDNw5R0m6MoGkCsUQKjDEkejRLcNp7EkSu\naO9MoDisy8VXyLazBXYzD0Vw/O3fjPfYQiLfcAJAIUNOXC8pMHH1l4Zj295jUGyNGrqgshCi33Ey\nQNmt3w1NIGSqmD62Agp11yRyiHNuyBlN6ayFTjfOErtsM50GQgE6L0mcHb5xiBx41hcg3IfAO2NJ\nD6wi8oVkKu029VAER3GEmicQ3iBHC/Ru/w4ADbVF2LHvOBTBEDRUdwghQfQXAV2BpnIca4+7XeN0\nVbh6nGRnzgkiV3DXGZLXZEd7jiM+1Tnfa6gUECLOGt+Ed3RN2Bd/We/J0P0MkUNpAaVFidwiuDxD\npAgOqgghvKLIzkxmOnx1/70QDIrCoasCN1wxdoCtIwY7HbGkW5HhaE8RHO2dNL+KGEBklWa3LnOO\nQ6RrAromMG5YsYcGEoMF3zhETqckzuUgQs4zXb6y+fbyKQNtGpFnyEiUnPOi00A3wiMys1/kMt3T\nN1c4h2IHkMooUETkgONR2VDG0aKpKSih5h3EAMEYA3fmsGVFhARlg4gc4BuHyMGZYZBIpMC578wj\nBjuWXavMAEU58bA3gsgVnAF1FaFemaGeGXNxgqARQfQXXfEUgMxmVFUyZUsEkWssy0Iqbbmlc84a\nqNLZNSIH+EZV2fXxnDEEDBUqXeyJgcZuKcsYoAoOlZp4EAOMkwli6L7+KT3WQ03lve4jiFzgZIh0\nVcHHh6IeW0PkCwFDnmNzzvUyJ2tOTjmRA3zjEDnI8xtyOvthu+UnQQwUYVN1F1/BGYTvviFEfpC5\n4Gt2NFTpIUZTU3rdRxD9xZDyEIL2sEvn7Iaqkt6IgYS5LbcZGBJJmbFsrC/y1ixiUOKr1a2qJACw\nzACu8iKqiycGltaOBLg7mJVDo3lDhAfsPxzNlMrZm9KeLY5NQ6HOSkTOKAnriHbJrq7OEGAqlyMG\nEmZ7QwwMjAOJpMyf0/gVIhf4yiE6fKzLbautcAZT811XcCIPEFwe2mxpi1FqnvCERCrt3nYOECs9\nzlQGDIX0SeSMCyZUubcdx4gzhh/9wyyvTCLyDLvBnCxlZ8CHu48C6J0tJ4j+4LQ9jq6uLtx66604\nevQogsEg7r33XhQXd295eM8992Dz5s0IBoNgjOEnP/kJQqHQ5z53IpVGPJmGYrc9pos9cSJyqUNm\nT4EbWhVGPJH+3McT+UkuNQjArZpzzrFpak+HSKWNAZEzHR4+3unedjJDwp57RRA9yYkO7WYKnAGc\nc5w/rhILz6+HQd1fiRxw2g7RL37xCzQ0NODGG2/Ec889h4cffhh33HFHt8d8+OGHWL9+PQoLC0/b\noJKIgdZoDIrg5BARJyRXOjQ1AVXhYIxh294WRKjLHHECcrkWBg3Fbaqg2k6P2sP5CRqKe76IyF9y\npcPsDoa79rfK++iaTJyAXOiQ2+khwRk4A1YtaqQyYSJnnPbVdPPmzZg9ezYAYNasWXjzzTe7/T6d\nTmPPnj248847sWzZMjz11FOn9fzO4TnOGTrtND1B9CRXOqytCMvsJAOunDkcC6bX97vtxOAgVxos\nCGqoKcu03RaCQRW8d1MFnZoqELnTYWdXyr09Y3wlAOruRZyYXOiQ2Rkiea4c5AwROeWkGaJf/epX\neOKJJ7rdV1JSgmAwCAAIBoNoa2vr9vvOzk40Nzfjq1/9KpLJJFauXInx48ejoaHh1K2SFUsoLaQB\ncMTA6pBBntlgDKgoDvTr+yC+uAykBieOKEF7ZwLtHQkAQDigQVUY2joT3R7HGcOVs4ed7VsjvkAM\npA6HV0fc287cF8oQEcDAX5O59Ir69T0QRE9O6hAtXrwYixcv7nbfTTfdhGhUziGIRqOIRCLdfm+a\nJpqbm6HrOnRdx3nnnYdt27Z9rujLysIAAENX0ZVIQTcUpBlz7x8oBvr1/GoD4B87BlKHbZ0JmKYK\nVVU8e/9++dzJjgwDqUHD0JBIA6oaAwCEw7ocVp2yen0Wufxs/PC5A/6www82AAOrw9KSzNmOUFAH\nABQXBuia7CF+sWMgdcgFh6YJJNO917+Bwi+fO9mRW077DFFTUxNee+01TJw4Ea+99hqmTp3a7fe7\ndu3CLbfcgmeeeQapVAp//vOfcdVVV33u8x46JKMJ8XgCqWQaR491YnRNgXv/QFBWFh7Q1/OrDX6z\noy9ypcNIQIUuONKptCfv30+fO9mRsaEvcqXBrq44YrEE9nwm33esK4FU2sLY+oFbD/3wufvFDj/Y\n4NjRF7nSIbfSqC0PYd/BdiTisny9oyNO12Syo8/7c6XDdDqNZDKNdJquyWRHxoZccNoO0bJly3Db\nbbdh+fLl0DQN999/PwDg8ccfR11dHebOnYsrr7wSS5YsgaIouOqqqzBixIhTeu7SAkOeH2IMHbEU\nqkuDp2sekSfkUodOVxuCOBm51CAYUBTS0NIeh6pw6KrA0KqCHL4b4otKrnRYXmjiG5ePxZ3/709Q\nFWF3+sr1uyG+qORKh12xlK09uigTuYVZlmV5bQQgM0SdsSQef34b2jvj+MsnrfjuV6YNqFPkF8/X\naxv8ZsdA8g/3/wFVJQF8drQDa5unfv4/6Gf89LmTHRkbBpINv/kAT/7hLyiO6DjaGsPK+Q144sXt\n+NltcwbsULEfPne/2OEHGxw7BpJDh9qw/0gUdzy2CddcOBzP/nE3brpmAsYPKxkwG/zw2fvBBr/Z\nMZBcvvpZjB9ejK5YCmubzxnQ1wb89bmTHRkbcoGv4j2mLievMzAkkmkUhXWvTSLyDEWR7d4ZHeAk\nPGLB9DoAwNFWeYbIkSJ1WCIGGicqrwgOxnq3fieIgYCDUU8FIuf4bnVzWiyu+8Z5NHyLGHD2fNYm\nnXJafAmfoFCpCOER3G533NqRABjomkx4AuMUECJyz2mfIco1jAGCU8tjwhu64ikwziBo8SV8Aucc\n69fM9doMIg8RnEEIhqNtXfZt38VQiTyAKjaIgcB3qxtjAKOIKOEhgjHSIOE544YVA5CDWQnCC1SF\ngzOG88ZWgDFGc4gIT+Cghh5E7vGdxBjo/AbhLZzThZ/wHqdEhKLyhFcwJq/HiuByQCati8QAo6sc\nYFQyR+Qe311pWzsS/jOKyCsYk445QXhJe2cCgCwhJggvMTSBtGVBU+gMETGwDK2KgDFGzjiRc3x3\nqQ0HVERjSa/NIPIYwRmY774ZRD4xt6kGh493AgA4iZHwCGcPqqsCpqZQ5pwYcJj9H2WIiFzjuyut\npgqY1MmG8BRGGSLCUwRnmDiiFACg0BkiwiOY3XGTc4aueIqi9MTAwzLdhwkil/jOIWJMziMiCC8Y\nO7SIJrITnvPh7hbXESKHiPAKRXA3Mp9MpWkcATHgcDtASesgkWt8t+2j1CjhJVUlst07RUIJLzF1\ngXTagiKoyQzhHZzLICVnDPFkGgodaCMGGgYcbYvROkjkHN+tbtTJhvCS5RePBsBoGCbhKUPKQviv\n9/aDMwZB6UrCIxizy4cZUF0ahK5SOTsxsOza34qyAgN0SSZyjS+vtOQQEV6RqZn35VeDyBP+tPWg\nvMGAaFfCW2OIvIUB7vyhA0c7vDaHyEM6YykIwWk2IJFzfLfrO9DSScfZCW9hFtXKE95i6y+ZTKOq\nOOCtLUTewhhDa0ccx9vjSKUtr80h8hTLshCPp7w2gxjk+M4hGlIeolpRwlN2728jDRKeErMv/mmL\nMuaEtwQNBaUFhtdmEHlKeZEJIThCAc1rU4hBju8cIg5QJIrwlDF1Rf77YhB5RfYaSLNfCC8xdQUG\ndX4lPKKhthCKYLQOEjnHl/s+U6eDm4R3cM6oXpnwlKGVYfc2ZYgILzl8vIs6vxKeMW9ard192GtL\niMGO7xyiT490ULkS4SmMgQ4QE56y+7M2AEB5oQmNOnsRHsMY8H9vnuW1GUQeMqQshEQqTUFKIuf4\nziGqKQti9/42r80g8hjOGOqzIvQE4RWMASrNfiE8hnOGkKl6bQaRp5i6QllKIuf47kqrKhyjaiNe\nm0HkOZSlJLxmdG0hDrR0Uskc4SmVxQHajBKe0hqN0xkiIuf47qRkPJFCWyfN3SC8I21ZVK9MeM5H\n+455bQJBwNCoZJPwloKghr/ub/XaDGKQ47sM0atbPoVBNfOEh7R3JKjTIeELhlVR6SbhLc55NoLw\nimhXEm0dFCgncovvHKKRNQUoCtPMA8I7RtcV4tPDUa/NIAhY5JcTBJHnFAQ1zBhf4bUZxCDHdw5R\nIpXG9r0tXptB5DEHjnbi/b8e9doMgqDoPEEQeU9BSIMiqHKIyC2+c4jGDStGlz2lnSC8IJZIobY8\n5LUZRB5TXmhi5oQqr80gCILwnPf/ehSvvfuJ12YQg5wzdoheeuklrF69us/fPfnkk7j66quxZMkS\nvPLKK6f1vK+88ym202Fi4hTJhQ7jiRT2HWzvJwuJfKC/dbhwRj3OH1/ZjxYSg51cXZMJ4nTIhQ7f\n23mkn6wjiBNzRl3m7rnnHrz++usYO3Zsr98dOnQIGzZswNNPP41YLIZly5ZhxowZ0DTtlJ57TF0h\nLjpnyJmYReQZudLhJdNqMaKmIBcmE4OQXOiwuiQIU1ewZsWUXJlNDCJyeU1+9NYv9bO1xGAlVzpc\neH49zm2kM0REbjmjDFFTUxPuuusuWH2c+H3vvffQ1NQEVVURCoVQX1+P7du3n/Jzf/WyRlwyrfZM\nzCLyjFzpMGComDC8pL/NJQYpudDhiJoCVJcGMbq2KBcmE4OMXF6TFRoMTJwiudLh1ReOoDJ2Iuec\nNEP0q1/9Ck888US3+9atW4fLLrsMmzZt6vPfRKNRhMOZVrHBYBDt7VR+RJw5pEPCD5AOCa8hDRJ+\ngHRIDEZO6hAtXrwYixcvPq0nDIVCiEYzLYuj0Sgikcjn/ruyMn/M2/CDHX6wAfCPHfmmQz/YAJAd\nPRkoHfrl/ZId/rIByL+1EPCHHX6wAfCPHfmmQz/YAJAduabfc+ETJ07E22+/jXg8jra2NuzcuROj\nRo3q75chiJNCOiT8AOmQ8BrSIOEHSIeE3zmjpgoAwBgDY8z9+fHHH0ddXR3mzp2LlStXYvny5Uin\n07jllltO+fAmQZwupEPCD5AOCa8hDRJ+gHRIfFFhVl+n3wiCIAiCIAiCIPIAah9DEARBEARBEETe\nQg4RQRAEQRAEQRB5CzlEBEEQBEEQBEHkLeQQEQRBEARBEASRt+TcIUqn0/jOd76DpUuXorm5GXv3\n7s31SwIA3n33XTQ3N7s/v/TSS1i9erX789tvv41rr70WS5YswX333dfvr59IJHDrrbdixYoVWLx4\nMV5++WVs3boVK1asQHNzM1atWoUjR44AAF599VUsWbIES5YswT333NNvNqRSKdx+++1YtmwZli9f\njh07dri/+/Wvf42lS5e6Pz/55JO4+uqrsWTJErzyyiv9ZkM2R44cwYUXXohdu3bhww8/xKxZs9Dc\n3Izm5mY8//zzAICNGzfimmuuweLFi937+gMvdEgalPhJh/mmQYB06EA6lOSjDkmDfeOVDvNRgwDp\nsC+8XAt7YeWYF1980VqzZo1lWZa1ZcsW6+/+7u9y/ZLWo48+ai1atMhasmSJZVmW9f3vf99asGCB\ndcstt7iP+fKXv2x9/PHHlmVZVnNzs/Xhhx/2qw1PPfWU9YMf/MCyLMs6duyYdeGFF1rXXXedtXXr\nVsuyLOuXv/yltW7dOqu9vd1atGiR1dLSYlmWZT3yyCPWkSNH+sWGl156yVq7dq1lWZa1adMm97P/\n4IMPrOuvv979fA4ePGgtWrTIisfjVltbm7Vo0SIrFov1iw0O8Xjc+uY3v2nNnz/f2rlzp/Xkk09a\n69ev7/aYI0eOWIsWLbKSyaTV3t5uXXjhhf32+gOtQ9JgBr/oMN80aFmkw2xIh5J81CFpsDde6jAf\nNWhZpMOeeL0W9uSM5xCdKps3b8asWbMAAJMmTcL777+P5uZmjBkzBjt27EAgEMDUqVPxxz/+Ea2t\nrVi/fj2OHDmC22+/HaqqIp1O4/7770dlZeUpv2Z9fT0eeughfPvb3wYANDU1Yd68efj3f/939zH/\n8R//Ac45otEo2tvbEQwGsWnTJjz66KPQNA2fffYZli5div/+7//Gtm3bsHLlSixbtgwPPvggNm3a\nhFQqhUsuuQQ33HBDnzYsWLAA8+fPByCjIYqi4MEHH0RpaSkAIJlMQtd1vPPOOxg9ejTuvfde7Nu3\nD4sXL0ZxcTF+9KMfYe/evWhpacGxY8ewYsUKvPjii9i9ezf++Z//GWPGjMHNN9+MaDSKzs5OfOtb\n38IFF1zQzYaLL74Yc+bMAQB88sknKCgoQEtLCx588EGsXbsWd955JwDgvffeQ1NTE1RVhaqqqK+v\nx/bt2/HKK6+ctQ0O//Iv/4Jly5bhkUceAQB88MEH2LVrF37/+9+jvr4ea9euRXFxMZ599llwznHw\n4EHoug4A/fJZDLQOSYMZ/KLDfNMgQDrMhnQoyUcdkgZ746UO81GDAOnQTxrsi5yXzLW3tyMUCrk/\nCyGQSqUwadIkPP7444jH4zBNE+vXr8fIkSPxpz/9CW+88QYmT56Mf/3Xf8VNN92Etra203rNSy65\nBEII9+fLLrus12M459iyZQsuv/xylJWVoaKiAgBw4MABPPTQQ7jrrrvw8MMP44c//CEee+wx90vz\n61//Gg888AA2btyISCRyQhsCgQCCwSDa29tx880341vf+pYr+s2bN2Pjxo34yle+gqNHj2LTpk24\n9dZb8dhjj+Hf/u3fsHv3bjDGYJomfvazn+GSSy7Bq6++ip/+9Kf4xje+gd/+9rfYt28fjh07hocf\nfhgPPPAAkslkn3YIIbBmzRr80z/9ExYuXIg77rgDa9asQSAQcB/T3t6OcDjs/uzY3V82PP300ygu\nLsbMmTPd+yZOnIjbbrsNP//5z1FbW4uHHnrI/bts3LgRS5cuxRVXXAEA/WLHQOuQNNgdr3WYjxoE\nSIc9IR3mpw5Jg93xWof5qEGAdJiN1xrsi5w7RKFQCNFo1P3Z8YrHjh0LAIhEIhg5cqR7Ox6PY/Hi\nxQiFQvj617+OjRs3dhNxfzJ58mS8/PLLaGxsxKOPPgrGGEaNGgUhBEKhEGpra6EoCiKRCGKxGADg\nvvvuw3333YdVq1ahtbX1pM+/f/9+XH/99bjyyiuxcOFCAMBzzz2Hu+66C48++iiKiopQVFSE8ePH\no6SkxI2KbN26FQBO+BnFYjGMHDkSS5cuxerVq3H33XfDOsl83XvvvRcvvPACvvnNb+Kjjz7CXXfd\nhdWrV+Mvf/kL1q1bh3A43O1vFI1G3S9Bf9jw9NNP44033kBzczO2bduGNWvWYPbs2e5zX3zxxe57\nBoAVK1bgj3/8I9566y1s2rSpX+zwqw7zRYOAtzokDZ4c0iHpcLDrkDSYwWsd5qsGAdKhg9ca7Iuc\nO0RNTU147bXXAABbtmxBQ0MDLMsCY+yE/+Z3v/sdpk6discffxzz58/HY4891q82WZaF5cuXu8IN\nBALgXH4UJ7MrHo/jhRdewAMPPIAnnngCzzzzDPbv39/nYw8fPoyvfe1ruPXWW3HVVVcBAJ599lls\n3LgRGzZswJAhQwDIP+iOHTvQ0tKCZDKJd9991/3DZtvbk48++gjRaBSPPPII1q1bh+9///u9HvOf\n//mfbirSMAyUlZXhueeew4YNG/DAAw9g5MiRuP322zFhwgS8/fbbiMfjaGtrw86dOzF69Oh+sQEA\nfv7zn2PDhg3YsGEDxowZg3vvvRd///d/j/feew8A8Oabb2L8+PHYtWsXbrzxRgCAoijQNM39u5yt\nHX7TYb5oEPCHDkmDfUM6JB3mgw5Jg93xWof5qEGAdJiN1xrsi5yfIZo3bx5ef/11t2vFD37wA3z3\nu9896b+ZMGECbrvtNjz88MNIp9NYu3btGb12togZY+7PjDGsWrUKN9xwAzRNQ3l5Oe655x68//77\nvf5N9m1N01BQUIBrr70Wuq5j5syZqKqq6vO1f/rTn6KtrQ0//vGP8eMf/xjpdBo7duxATU2N+8ed\nPn06brzxRqxevRqrVq0CINO4o0aNwosvvtjN3p7va+jQoXjooYfw/PPPI51O4+abb+5lw4IFC7Bm\nzRpcd911SCaTuOOOO6BpGgB0W3zKysqwcuVKLF++HOl0Grfccov7uLO1oS8YY7j77rtx9913Q1EU\nlJeX43vf+x6CwSDGjBmDJUuWgDGG2bNnY9q0adi0adNZ2+GVDvNdg4A/dZhPGuxpM+mQdJhvOiQN\nnpyB1mE+ahAgHZ4ML9bCXjZYp5JHIgiCIAiCIAiCGITQYFaCIAiCIAiCIPIWcogIgiAIgiAIgshb\nyCEiCIIgCIIgCCJvIYeIIAiCIAiCIIi8hRwigiAIgiAIgiDyFnKICIIgCIIgCILIW8ghIgiCIAiC\nIAgib/n/mZ9nEBZBAPMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c46bed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i, x in enumerate(kick_signals):\n",
    "    plt.subplot(2, 5, i+1)\n",
    "    librosa.display.waveplot(x[:10000])\n",
    "    plt.ylim(-1, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Display the snare drum signals:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0QAAAE5CAYAAACwOuAYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJIQQQgghhIhYUhAJIYQQQgghItb/BwibGPt0oI1JAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d724850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i, x in enumerate(snare_signals):\n",
    "    plt.subplot(2, 5, i+1)\n",
    "    librosa.display.waveplot(x[:10000])\n",
    "    plt.ylim(-1, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Constructing a Feature Vector"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A *feature vector* is simply a collection of features. Here is a simple function that constructs a two-dimensional feature vector from a signal:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def extract_features(signal):\n",
    "    return [\n",
    "        librosa.feature.zero_crossing_rate(signal)[0, 0],\n",
    "        librosa.feature.spectral_centroid(signal)[0, 0],\n",
    "    ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we want to aggregate all of the feature vectors among signals in a collection, we can use a list comprehension as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "kick_features = numpy.array([extract_features(x) for x in kick_signals])\n",
    "snare_features = numpy.array([extract_features(x) for x in snare_signals])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualize the differences in features by plotting separate histograms for each of the classes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10e04f750>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAz8AAAFICAYAAAB+7UATAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e449710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(kick_features[:,0], color='b', range=(0, 0.1))\n",
    "plt.hist(snare_features[:,0], color='r', range=(0, 0.1))\n",
    "plt.legend(('kicks', 'snares'))\n",
    "plt.xlabel('Zero Crossing Rate')\n",
    "plt.ylabel('Count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10d235850>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0kAAAFICAYAAACFurXMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAMCCkAQAAAAAFoQkAAAAALD4/wGEWHgW4cJYFQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e1d2c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(kick_features[:,1], color='b', range=(0, 4000), bins=40, alpha=0.5)\n",
    "plt.hist(snare_features[:,1], color='r', range=(0, 4000), bins=40, alpha=0.5)\n",
    "plt.legend(('kicks', 'snares'))\n",
    "plt.xlabel('Spectral Centroid (frqeuency bin)')\n",
    "plt.ylabel('Count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature Scaling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The features that we used in the previous example included zero crossing rate and spectral centroid. These two features are expressed using different units. This discrepancy can pose problems when performing classification later. Therefore, we will normalize each feature vector to a common range and store the normalization parameters for later use.  \n",
    "\n",
    "Many techniques exist for scaling your features. For now, we'll use [`sklearn.preprocessing.MinMaxScaler`](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MinMaxScaler.html).  `MinMaxScaler` returns an array of scaled values such that each feature dimension is in the range -1 to 1."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's concatenate all of our feature vectors into one *feature table*:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(20, 2)\n"
     ]
    }
   ],
   "source": [
    "feature_table = numpy.vstack((kick_features, snare_features))\n",
    "print feature_table.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scale each feature dimension to be in the range -1 to 1:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-1. -1.]\n",
      "[ 1.  1.]\n"
     ]
    }
   ],
   "source": [
    "scaler = sklearn.preprocessing.MinMaxScaler(feature_range=(-1, 1))\n",
    "training_features = scaler.fit_transform(feature_table)\n",
    "print training_features.min(axis=0)\n",
    "print training_features.max(axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the scaled features:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10e2dda50>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0oAAAFICAYAAABujQ7PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n3xAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e2f4250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(training_features[:10,0], training_features[:10,1], c='b')\n",
    "plt.scatter(training_features[10:,0], training_features[10:,1], c='r')\n",
    "plt.xlabel('Zero Crossing Rate')\n",
    "plt.ylabel('Spectral Centroid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[&larr; Back to Index](index.html)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
